Error messages reference

The most important error messages and warning messages are listed according to their four-digit error code numbers in ascending order. Typically, each message contains a description of the error event, an explanation, why the error occurred, and the action you need to do to solve the problem.

IDM1077 No parameter can be NULL, except CALLID.

User response

Enter non-NULL values for the relevant parameters.

IDM1078 The specified target field value is out of range.

IDM1101 For the method "%1", the input model is not valid. Valid models for this method are PMML models of the type "%2".

IDM1102 The input model is not a PMML model of a supported model type. Supported model types are AssociationModel, ClusteringModel, MiningModel, NeuralNetwork, RBFModel, RegressionModel, SequenceModel, NaiveBayesModel, TreeModel and TimeseriesModel.

IDM1103 While parsing an association rule model or a sequence rule model for the method "%1", an error occurred. The model is not a rule model, or it is damaged.

Explanation

The parser's error message is: "%2".

IDM1106 While parsing a Clustering model, an error occurred. The model is not a Clustering model, or it is damaged. Generate the model again.

IDM1107 While parsing a Classification model for the method "%1", an error occurred. The model is not a Classification model, or it is damaged.

Explanation

The parser's error message is: "%2".

IDM1108 An error occurred when a model for the method "%1" was parsed. The model is not a Regression model, or it is damaged.

Explanation

The error message of the parser looks like this: "%2".

IDM1109 An error occurred when a rule filter for the method "%1" was parsed. The rule filter is invalid, or it is damaged.

IDM1127 The Classification model or the Regression model that you are using does not contain a target field.

Explanation

The mining schema of the model must contain a mining-field entry for the target field. The usageType attribute of this entry must have the value 'predicted'.

IDM1191 The field "%1" already exists.

IDM1192 A field with the name "%1" is not available.

IDM1193 There is no field available at position "%1".

IDM1194 A fieldtype is wrong.

IDM1219 There is no category map available at position "%1". The number of defined category maps is "%2".

Explanation

The position value represents the map number. Values start at 1. A value cannot be greater than the number of maps.

User response

Use the method DM_getNumTaxMap to check how many maps are available. Then specify as the position a number that is greater than 1 and less than or equal to the number that DM_getNumTaxMap returns.

IDM1220 There is no taxonomy available at position "%1". The number of defined taxonomies is "%2".

Explanation

The position value represents the taxonomy number. Values start at 1 and cannot be greater than the number of taxonomies.

User response

Use the method DM_getNumTax to check how many taxonomies are available. Then specify as the position a number greater than 1 and less than or equal to the number that DM_getNumTax returns.

IDM1221 The taxonomy "%1" has no category map.

IDM1222 The field type is incorrect. Valid field types are 0 (categorical), 1 (numeric), or 2 (multi valued categorical).

User response

Correct the field type, and call the method again.

IDM1223 The argument of the function 'compatibleData' is not a valid description of a logical data specification.

IDM1224 The Intelligent Miner Classification mining function does not support the algorithm "%1".

Explanation

For classification, the algorithms "Tree", "NaiveBayes" and "Logistic" are supported.

IDM1225 The Intelligent Miner Clustering mining function does not support the algorithm "%1".

Explanation

For clustering, the algorithms "Demographic" and "Kohonen" are supported.

IDM1226 The Intelligent Miner Regression mining function does not support the algorithm "%1".

Explanation

For regression, the algorithms "Linear", "Polynomial" and "Transform" are supported.

IDM1227 The Intelligent Miner rules mining functions do not support the algorithm "%1".

IDM1233 The function "DM_setFldUsageType" cannot modify the usage type of the mining field "%1" because this field is either the target field of a classification or regression task, or a group or item field of a rule task.

IDM1234 An illegal reference was made to a non-existing "%1" with the name "%2" in the function "%3".

Some parts of the mining settings consist of lists of elements. For example, there can be several field usage entries. Many of these list elements can be accessed by means of the DM_get... functions. These take the position in the list as one of their parameters. This error message is issued if the value of a position parameter goes outside the valid range. This range extends from 1 to the number of items in the list.

User response

Change the value of the position parameter to a valid value.

IDM1238 The attribute "%1" of the XML element "%2" is undefined, and cannot be accessed.

Explanation

An attempt was made to access some mining settings information. This information is stored in the form of an attribute to an XML element in the XML representation of the current settings. However, the mining settings do not contain the desired attribute. This error message occurs only when parts attributes for which there are no default values available are being accessed.

User response

Define the desired attribute before trying to retrieve it.

IDM1239 The definition of a new weight or similarity matrix failed because one of the required attributes is missing (name, table name, actual value column, predicted value column, or weight column).

You can specify the usage types "target", "group", or "item" only for categorical fields.

User response

Set the field type attribute of the mining field to "categorical" and specify the usage type that you want to use.

IDM1244 There is no cost or similarity matrix with the name "%1".

IDM1245 There is no cost or similarity matrix available at position "%1".

IDM1246 The field "%1" is not numeric. The usage type of this field cannot be defined as target, weight, or variance for regression or time series.

IDM1249 An invalid cost value is specified for the actual value "%1" and the predicted value "%2". Valid cost values are non-negative. If the actual value and the predicted value are identical, only zero is a valid cost value.

IDM1266 The definition of a new mining task failed because the validation data are incorrect.

IDM1267 The definition of a new mining task failed because the mining settings are incorrect.

IDM1268 The mining task is not valid. Either it contains XML syntax errors or the logical data specifications are incompatible with the mining data.

A season can be set for each time series target field. The specified field must not be "NULL" and also must have been specified in the settings.

User response

Specify a valid field name that has already been specified by the "DM_addTsTarget" method.

IDM1601 The codepage %1 is not supported.

IDM1602 The initialization of the trace facility failed. No trace messages will be written.

Check the field specifications in your filter record conditions, value mapping objects, discretization objects, or computed fields.

IDM2023 The Intelligent Miner is unable to create result object "%1".

User response

Check the available disk space in the output directory. Also check whether you have a write permission for that directory.

IDM2024 An empty result file name has been specified.

IDM2025 In the result "%1" the basic statistics of field "%2" has not been computed yet.

IDM2026 The descriptive statistics result "%1" contains fields with incomplete statistics.

IDM2027 The index for partition "%1" is out of range; it has to be between 0 and %2.

IDM2028 The flat file or database table "%1" related to name-mapping object "%2" cannot be opened.

User response

Check if the file or table still exists, and if you have read permission for the drive on which it is located.

IDM2029 The flat file or database table "%1" related to value-mapping object "%2" cannot be opened.

User response

Check if the file or table still exists, and if you have read permission for the drive on which it is located.

IDM2038 The Intelligent Miner is unable to read the result object "%1".

User response

Check if the file exists, and verify that you have read permission on the server.

IDM2039 The labels for the classification result object "%1" exist already and cannot be updated.

IDM2040 The label "%1" is unknown to the classification result object "%2".

Change the input values for the similarity matrix so that the matrix becomes symmetric.

IDM2081 The number of rows and columns "%1" of the similarity matrix in the clustering result object "%2" is not equal to the number of clusters "%3".

Explanation

The results are incorrect.

IDM2082 The frequency value "%1" for out of range values of a discrete statistics object is negative.

IDM2083 The sum of frequency values (including those that are out of range) "%1" of a discrete statistics object is greater than the value of the total frequency "%2".

IDM2084 The negative frequency "%1" exceeds the total frequency "%2".

IDM2085 "%2" values were defined as valid values for the binary field "%1". However, the number of possible values of a binary field must be 2. Define 2 values as valid values for the binary field "%1".

IDM2091 For this pass, the Intelligent Miner interpreted the values of field "%1" as continuous values. Therefore, the "%2" out-of-range values in your list of valid values were ignored because valid values can only be used with categorical and discrete-numeric data. However, your list of valid values might be considered during a subsequent pass.

IDM2097 The message file "%1" cannot be created. Check if you have write permission for the file and the directory in which it is to be located.

IDM2099 "%1".

IDM2100 The buffer has been extended to %1 characters.

IDM2103 The lowest histogram limit %1 is not smaller than the highest limit %2.

IDM2109 Invalid continuous statistics object for field "%1".

IDM2110 Invalid discrete statistics object for field "%1".

IDM2111 The discrete statistics object is missing for field "%2" that has been used for initializing the descriptive statistics result "%1".

IDM2112 The continuous statistics object is missing for field "%2" that has been used for initializing the descriptive statistics result "%1".

IDM2113 To start the calculation of the descriptive statistics result "%1", the field "%2" is used. In the next pass over the data, complete continuous statistics cannot be computed for the field "%2" .

IDM2114 The discrete statistics has not yet been computed for the numeric field "%2" that has been used for initializing the descriptive statistics result "%1";

Explanation

as it possible that the field type changes to continuous within the next pass it is not certain that the statistics will be complete after the end of the next pass.

IDM2115 The descriptive statistics result "%1" is initialized already; it is not possible to initialize it a second time.

IDM2116 The descriptive statistics result "%1" of partition "%2" is not initialized yet.

IDM2117 The fieldtype in the result file is not applicable for Field "%1".

IDM2118 A field with the name "%1" does not exist in result object "%2". Remove the field "%1" from the list of input fields in your settings object.

IDM2119 The active field "%1" is not declared as an active field in the statitics of the result object. In the corresponding settings object, change the status of the field to supplementary, or remove it from the list of input fields.

IDM2120 The field "%1" was used to construct the model. Therefore, it must be defined as an active field in test or application mode. Add the field "%1" to the list of active fields in the corrsponding settings object.

IDM2121 The value mapping object "%1" is in an inconsistent state.

IDM2122 Data cursor "%1" of value mapping "%2" cannot be rewound.

IDM2125 The result statistics do not identify the field "%1" as the field to be predicted. Choose the correct field as the prediction field.

IDM2126 The bucket number "%1" is less than or equal the minimum long integer. This number has been computed for the value "%2" and bucket width "%3".

IDM2127 The bucket number "%1" is greater than the maximum long integer. This number has been computed for the value "%2" and bucket width "%3".

IDM2130 The memory limit is reached.

Explanation

More memory is not available.

User response

You can do one of the following actions: Increase the maximum of memory available to Intelligent Miner by specifying a larger value via the power option '-buf'. Specify less fields with usageType systemDetermined in your mining settings.

IDM2168 The number of valid values "%1" for a continuous statistics object is negative.

IDM2169 The number of valid values "%1" for a continuous statistics object is greater than the value for total frequency "%2".

IDM2170 A field name specified as an argument is NULL.

IDM2171 A numeric field with the name "%1" does not exist in result object "%2".

User response

Remove the field "%1" from the list of input fields in your settings object.

IDM2186 The status file "%1" cannot be opened in write-mode. System error %2: %3.

IDM2187 No name was given for a status file. No status info will be written.

IDM2188 Status file is in bad state.

IDM2189 Unable to rewind status file. System error %1: %2.

IDM2190 Unable to write to status file. System error %1: %2.

IDM2191 Unable to open file %1. System Error %2: %3.

IDM2192 Unable to open file %1.

IDM2193 Unable to close file. System Error %1: %2.

IDM2194 Unable to close file.

IDM2195 Unable to rewind file. System Error %1: %2.

IDM2196 Unable to rewind file.

IDM2197 Could only write %1 out of %2 KB to a file. System Error %3.

IDM2198 Could only write %1 out of %2 KB to a file.

IDM2199 Could only read %1 out of %2 KB from a file. System Error %3.

IDM2200 Could only read %1 out of %2 KB from a file.

IDM2201 Not enough main memory available for temporary record buffer. Remaining space was less than %1 KB.

IDM2202 Can not find a name for a temporary file. System Error %1: %2.

IDM2203 Can not find a name for a temporary file.

IDM2204 The Intelligent Miner cannot sort the data because the number of records is unknown. Note that pipes and random samples cannot be sorted.

IDM2213 The string "%1" cannot be written to the result object because it contains a new-line character. The record length might be incorrect.

User response

Compare the field descriptions in your data object with the field lengths in your input data. Correct the record length in the data object, if necessary.

IDM2216 Active field "%1" occurs more than once.

IDM2224 The statistics in the result are incomplete. Therefore the description of field "%1" in cluster "%2" cannot be calculated.

IDM2303 An SQL error occurred: SQLstate: "%1", SQL Error Message: %2. See the DB2 User's Guide or the Message Reference.

IDM2304 An SQL error occurred: Executing "%1" SQL returned "%2". See the DB2 User's Guide or the DB2 Message Reference.

IDM2305 The table "%1"."%2" does not exist.

IDM2306 The number of columns "%1" is negative or exceeds the maximum number of columns per table.

IDM2307 Column "%1" has type "%2", which is not supported for data mining.

IDM2308 The table "%1"."%2" does not contain the column "%3".

IDM2309 Function sequence error. An Open must precede a getNextRecord or a skipRecord.

IDM2318 DB access protocol: Number of rows fetched: %1, rejected: %2, (SQLSTATE: 22003, 22005).

IDM2320 No records were returned for a SELECT statement. Either the table "%1"."%2" is empty or record filter conditions were specified that do not match any of the records in the table.

IDM2321 The index "%1" on table "%2"."%3" cannot be recreated.

IDM2322 Column "%1": The type conversion from "%2" to "%3" is not supported.

IDM2323 Table "%1"."%2" has not enough columns to append output table records.

IDM2324 Column "%1" in table "%2"."%3" has a datatype that is not supported by DataAccessAPI.

IDM2325 Output field "%1" does not exist in table "%2"."%3". Append cannot be performed.

IDM2326 Column "%1" in table "%2"."%3" is not nullable. Append cannot be performed.

IDM2333 Input buffer has already been created. Can not open a new one before the first has been closed.

IDM2334 Updatable buffer has already been created. Can not open a new one before the first has been closed.

IDM2335 Data has already been read from the data source. The lookaside buffer might be inconsistent.

IDM2336 The input size for the input buffer cannot be determined.

IDM2337 You can update the buffer. However, the input size for the buffer cannot be determined.

IDM2338 The lookaside buffer cannot be created.

IDM2340 The lookaside buffer's field list is empty.

IDM2342 You can update the buffer. It was attempted to access the updatable buffer before creating it.

IDM2343 Input buffer is not ready for use in method "%1".

IDM2344 Updatable buffer is not ready for use in method "%1".

IDM2345 No working directory has been set in parameter file. Using /tmp for lookaside buffer files.

IDM2346 Read error on input buffer file "%1". System error code: "%2".

IDM2347 Read error on updatable buffer file "%1". System error code: "%2".

IDM2348 Write error on input buffer file "%1". System error code: "%2".

IDM2349 Write error on updatable buffer file "%1". System error code: "%2".

IDM2350 Seek error on input buffer file "%1". System error code: "%2".

IDM2351 Seek error on updatable buffer file "%1". System error code: "%2".

IDM2352 The updatable and the input buffer have a different number of entries.

IDM2353 The lookaside buffer has read %1 but expected %2 records from the data source. May run out of diskspace.

IDM2354 The lookaside buffer has read %1 but expected %2 records from the data source. This is probably due to filtering or modified database tables.

IDM2490 File "%1" has experienced an I/O error. Diagnostic information follows:

IDM2491 lastop=%1, errno=%2, syscode=x'%3', rc=%4

IDM2492 errno message: %1

IDM2493 An abend has occurred (signal SIGABND): code=x'%1', reason=%2

IDM2494 A signal %1 ('%2') has occurred causing abnormal termination.

IDM2496 Error during XML parser initialization: %1.

IDM2497 XML parser error in %1. Line: %2, Column: %3, Message: %4.

IDM2498 The XML element %1 is not unique. Specify a unique name for this element.

IDM2500 An XML syntax error occurred in the input record %2 at the position %1.

Explanation

The input format for the DM_ApplicationData record is not valid, or the record is empty. One of the column values might contain invalid XML characters such as '<' or '&'. For example, for '<' you must use < or for '&' you must use &.

User response

Check the input record against the XML DTD of Intelligent Miner. Replace the invalid characters with the appropriate coding.

IDM2501 The value %1 of the field %2 in the XML input record cannot be converted to a numeric value.

IDM2545 The input model is not a valid PMML model. The following errors occurred: %1 %2 %3.

IDM2546 The input model contains invalid references between XML elements. The following errors occurred: %1 %2 %3.

IDM2547 Test mode is only supported for tree classification models or for transform regression models.

The function %1 is used at a place where a numeric value is expected. This model is not a valid PMML model.

IDM2561 The function %1 is not categorical.

Explanation

The function %1 is used at a place where a categorical value is expected. This model is not a valid PMML model.

IDM2562 The function "%1" takes %2 arguments. It does not take %3 arguments.

Explanation

A call to the function %1 presents %3 arguments. However, the function has only %2 arguments. This model is not a valid PMML model.

IDM2563 The input PMML model is not suitable for general regression.

Explanation

Suitable PMML models for general regression must contain a <GenearlRegression> tag.

IDM2600 The name mapping %1 is not complete.

IDM2610 The XML parameters do not contain a valid task element.

IDM2611 The XML parameters do not contain the mining data element %1.

IDM2612 The XML parameters do not contain a logical data specification.

IDM2613 The XML parameters do not contain settings.

IDM2614 The XML parameters do not contain clustering settings.

IDM2615 The XML parameters do not contain classification settings.

IDM2616 The XML parameters do not contain association rules settings.

IDM2617 The XML parameters do not contain regression settings.

For numeric fields, a non-outlier range can be specified by giving a lower and an upper boundary. Because only one of these limits has been specified, the limit will be ignored.

User response

Either specify no limits, or specify the lower and upper boundaries.

IDM2631 There is a reference to the weight information %1 for the field %2. However, the weight information does not exist.

User response

Remove the reference to the weight information %1 in the field %2, or specify the weight-information %1.

IDM2632 The weight information %1 is not complete.

User response

Verify that you have specified a weight-information name, a table name, and two column names.

IDM2635 The value %2 of power option %1 is not valid.

Fix the cause of the error and try again.

IDM2750 The error message table %2 in the schema %1 does not exist.

IDM2751 The number of columns in the error message table %2 in the schema %1 cannot be retrieved.

IDM2752 The names of the columns in the error message table %2 in the schema %1 cannot be retrieved.

IDM2753 The error message table %2 does not contain all the necessary columns. The following columns are missing: %1.

IDM2754 The SQL types of some columns in the error message table %2 are not correct. The following columns have incorrect types: %1.

IDM2755 Old error messages cannot be deleted from the error message table %1.

IDM2756 An error message cannot be inserted into the error message table %1.

IDM2760 The progress information table %2 in the schema %1 does not exist.

IDM2761 The number of columns in the progress information table %2 in the schema %1 cannot be retrieved.

IDM2762 The names of the columns in the progress information table %2 in the schema %1 cannot be retrieved.

IDM2763 The progress information table %2 does not contain all the necessary columns. The following columns are missing: %1.

IDM2764 The SQL types of some columns in the progress information table %2 are not correct. The following columns have incorrect types: %1.

IDM2765 Old progress information cannot be deleted from the progress information table %1.

IDM2766 Progress information cannot be inserted into the progress information table %1.

IDM2767 Progress information cannot be selected in the progress information table %1.

IDM2768 The mining run was cancelled.

Explanation

The mining run is cancelled. No model is written.

IDM2770 The codeset of the system is %1. This codeset cannot be processed.

IDM2771 You are using a temporary license. You must enroll "%1" within "%2" days in the license file "%3".

User response

Buy a production license and replace the nodelock files, or uninstall the product after the temporary license has expired.

IDM2772 You are using a temporary license. The number of days left is "%2". You must enroll "%1" in the license file "%3".

IDM2776 The license for the product "%1" was found in the file "%2".

IDM2777 The product "%1" does not have a license enrolled. Check your installation. If you have not purchased a license for this product, you may select 'CONTINUE' to enroll an evaluation license. PLEASE READ THE EVALUATION PROGRAM LICENSE AGREEMENT CAREFULLY. IF YOU SELECT 'CONTINUE', THIS WILL CONSTITUTE YOUR ACCEPTANCE OF THESE TERMS AND APPLICABLE COPYRIGHT LAWS. IF YOU DO NOT ACCEPT THESE TERMS, SELECT 'EXIT'. 1. EXIT 2. CONTINUE

IDM2800 An invalid handle is returned by DB2.

IDM2801 A DB2 error occurred. There is no explanation available. See the db2diag.log file for details. Check that the DB2INSTANCE environment variable is set correctly and that the appropriate DB2 runtime library, for example, libdb2.a for DB2 on AIX, is accessed.

IDM2802 An error occurred while processing a previous DB2 error. Make sure that the DB2INSTANCE environment variable is set correctly and that the correct DB2 runtime library is accessed.

User response

Contact your IBM representative.

IDM3104 The Parallel Operating Environment cannot start a task.

IDM3105 The clustering process stopped because the model did not improve during the last pass.

Contact your IBM representative.

IDM3111 The field "%1" is specified as an active field more than once, or it is specified as an active and as a supplementary field.

Explanation

The field is used as an active field only once. Any other specifications are ignored.

IDM3112 Error when opening 'Result Statistics.'

IDM3113 The field "%1" does not appear in the result statistics.

Explanation

Therefore, the Intelligent Miner cannot use these result statistics to apply the model to your current data.

User response

Check the input fields you specified and the result statistics. Correct any mismatch. If there is no mismatch, Contact your IBM representative.

IDM3116

Explanation

To run this function in application mode, you must specify output fields.

IDM3117 The active field "%1" is not defined as an active field in the result statistics.

IDM3129 The MPI-call -%1- was not successful. The returncode was %2.

User response

Contact your IBM representative.

IDM3130 The indicator received by the function IDMPSendRecordMsg::Send is not valid.

User response

Contact your IBM representative.

IDM3131 The function (%1) received a message from a node that is not involved in the current process.

User response

Contact your IBM representative.

IDM3132 The function (%1) detected a messageholder that is not valid.

User response

Contact your IBM representative.

IDM3135 A faulty record has been found and skipped.

IDM3136 The field "%1" was not used when the model was built.

User response

Remove this field from the active fields list.

IDM3137

Explanation

Supplementary fields are ignored in application mode.

User response

This is just an information and requires no action on your part.

IDM3141 The order of the best records is incorrect.

User response

Contact your IBM representative.

IDM3142 The value for the similarity threshold was not between 0 and 1. Therefore, the default value of 0.5 is used.

IDM3143 You are using a Version 1 result for application mode.

Explanation

This result does not contain distance units. Default distance units are calculated and used.

IDM3144 An error occurred while writing to the output table.

IDM3145 An error occurred while writing the best records.

IDM3146 The discrete numeric field "%1" has %2 different values.

Explanation

Consequently, the similarity matrix for this field needs a lot of space, which might cause your system to run out of memory.

User response

It is recommended that you define this field as a continuous field.

IDM3147 You are converting a Version 1 result to XML. This model does not contain distance units.

The clustering run will terminate immediately. No model will be written.

IDM3181 There is not enough time to process the clustering run.

Explanation

An estimate that %1 seconds of processing time are necessary has been made after %3 seconds of execution. However, a time of only %2 seconds has been specified by the user.

User response

Increase the maximum desired execution time, or decrease the percentage of data to be read.

IDM3182 The type for field %1 has been changed to supplementary.

Explanation

The type for field %1 was not appropriate to the demographic clustering algorithm. From now on, it is treated as supplementary, and is not used to find clusters.

To determine the boundary values for the bins of the test result's Lift chart, the Lift data in the input model must be correct. Binning might not be possible, because the training data might contain only one target field value.

IDM3409 The test data cannot be accessed in Transform Regression test mode.

IDM3410 An internal error occurs while the Transform Regression model is trained.

User response

See the Intelligent Miner trace file. To create a trace file, make sure that the environment variable IDM_MX_TRACELEVEL is specified as 'BASIC', 'MOST', or 'ALL'.

IDM3411 An internal error occurs while the Transform Regression model is tested.

User response

See the Intelligent Miner trace file. To create a trace file, make sure that the environment variable IDM_MX_TRACELEVEL is specified as 'BASIC', 'MOST', or 'ALL'.

IDM3412 The Lift chart validation of this model results in a ranking quality that is worse than the ranking quality of a random model.

User response

Use the generated model with precaution.

IDM3413 The numeric distributions for the target field '%1' cannot be determined.

Explanation

The target field might contain missing or incorrect data values.

User response

Ensure that the target field contains correct data values.

IDM3414 Bins for the target field values cannot be created.

User response

Make sure that the target field is not a single-valued field. This means that the training data should contain at least two different correct target field values.

IDM3415 A parallel data scan of the training or the validation data cannot be started.

IDM3441 The specified maximum processing time is too small to build a model. With the current training data, Intelligent Miner needs about %1 minutes to build a complete model.

User response

Specify a larger time limit in method DM_setExecTime, or reduce the amount of input data, for example, by sampling.

IDM3450 The model or the test result is correct, however, only part of the additional explanatory information can be created.

Explanation

Information about the following parameters cannot be created: field importance, lift chart, accuracy, quality, or field-field correlation coefficients. The generated model or test result might not contain active mining fields.

IDM3480 The input PMML model for Transform Regression scoring or test is not a correct Transform Regression model.

Explanation

A well-formed Transform Regression model is a correct XML document with the root tag <PMML> and the mandatory subtags <Header>, <DataDictionary>, and <MiningModel ... algorithmName="Transform Regression">.

IDM3481 The input PMML prediction model for scoring or test does not contain a correct target field.

Explanation

A correct prediction model contains the tag <MiningField name="???" usageType="predicted"> inside the subtag <MiningSchema>. The name of the field "???" must be equal to the 'displayName' attribute of a <DataField> tag within the <DataDictionary>.

IDM3482 The input PMML model for prediction scoring or test contains the unexpected XML tag <%1>.

IDM3491 The input PMML model for decision-tree scoring or test defines the missing value strategy 'defaultChild', however, in the internal tree node with the ID %1 the required attribute 'defaultChild' is missing or invalid.

IDM3515 There are too many taxonomy levels, or the taxonomy is cyclic.

Explanation

Intelligent Miner does not accept more than 255 taxonomy levels or cyclic taxonomies.

IDM3516 For the item field value %3, the name mappings %1 and %2 are defined. The second name mapping is ignored.

Explanation

For the same field, only one name mapping is allowed.

User response

To avoid this warning message, delete one of the name mappings.

IDM3517 The field values %1 and %2 are mapped to the same value %3.

Explanation

You can map different item field values to the same name mapping, however,this might lead to unexpected results. For example, when opening the created model in the visualizer, you might find two identical rules containing the mapped value.

IDM3518 %1 is not a correctly formatted multi-item XML string.

IDM3540 A cancel request is issued while creating the association or sequence rule model.

Explanation

The training run terminates immediately. A model is not created.

IDM3541 The specified maximum execution time is too small to build a model. With the current training data, Intelligent Miner needs about %1 minutes to build a complete model.

User response

Specify a larger time limit in method DM_setExecTime, or reduce the amount of input data, for example, by sampling.

IDM3580 The PMML model is not a valid Association Rule model or Sequence Rule model.

Explanation

IDM3587 The PMML rule model contains expressions that cannot be interpreted.

User response

See the Intelligent Miner trace file. To create a trace file, make sure that the environment variable IDM_MX_TRACELEVEL is specified as 'BASIC', 'MOST', or 'ALL'.

IDM3588 The PMML model contains an empty item without a value.

IDM3590 The following input data record is malformed and cannot be parsed: %1.

IDM3591 The input data record contains expressions that cannot be interpreted. These expressions are ignored. The ignored XML tags and attributes are %1.

IDM3592 The input data record contains an empty item value.

IDM3610 The test data cannot be accessed in logistic regression test or training.

IDM3611 Gains charts cannot be computed because the data contains less than two target values.

IDM3640 Data is read.

IDM3641 A model is built.

IDM3642 The generated model is validated.

IDM3643 The logistic regression training process finished.

IDM3660 The time series %1 is too short for analysis.

Explanation

A series can be too short because the absolut number of samples is too small. The season might be set too large for a small number of series samples.

User response

Get more samples or set the season to a lower value.

IDM3661 Seasonality is not possible.

IDM3662 There are too many missing values for series %1.

IDM3663 The interpolation mode for the time stamps is not valid.

IDM3664 The time settings "from time", "to time", or "forecast horizon" have different types.

Explanation

If time settings are set, they must have the same type, for example, TIME ("14:23:45"), DATE("2007-11-23"), TIMESTAMP("2007-11-23-23.44.33.234533"), or numeric("24.3566").

User response

Set all time settings to the same type, or reset them to NULL.

IDM3665 The order of the time settings is not correct. "%1" must be larger than "%2".

Explanation

If time settings are used, they must have the following order: "from time" lower than "to time" lower than "forecast horizon".

IDM3666 The time series is too long for the Seasonal Trend Decomposition algorithm. The calculation of the forecast is omitted.

IDM3667 The season for series "%1" is set to a larger value than the time series size range.

Explanation

To enable useful forecasts, the time series size must be at least as long as the season size.

User response

Set the season size to at maximum the range of the time series.

IDM3676 The time field is not specifed.

Explanation

The time field defines the order of the series. It is mandatory for the analysis.

User response

Specify a valid time field in the time series settings.

IDM3677 No series can be processed. A model is not created. For details see previous warnings and errors.

IDM3701 The Naive Bayes classification-training run cannot be started because the input settings are not correct.

Explanation

Make sure that the settings contain correct training data.

IDM3702 The Naive Bayes test run cannot be started because the input settings are not correct.

Explanation

Check the input settings. Training settings might be provided instead of test settings. The settings might contain an incorrect PMML model or incorrect test data.

IDM3703 The generated model cannot be exported into PMML format.

User response

Contact your IBM representative.

IDM3704 The Naive Bayes mining task needs more than the specified amount of memory.

User response

Increase the memory limit by using the power option '-buf [size in MB]', or reduce the complexity of the mining task.

IDM3705 When the Naive Bayes classification model was created, a cancel request was issued .

Explanation

The training run stopped. A model was not created.

User response

Make sure that the schema name and the table name that are specified in the mining task exist, and that they can be opened for reading.

IDM3706 The specified maximum processing time is too small to build a Naive Bayes classification model. With the current training data, about %1 minutes are required to build a complete model.

User response

Specify a larger time limit in the method DM_setExecTime, or reduce the amount of input data, for example, by sampling.

IDM3708 The number of values in the target field is either too high, or the target field of the test set contains values not present in the training set.

User response

For training: use the -IDM_MAX_DISCR_COUNT power option to increase the number of allowed categorical values. For testing: make sure that the test set does not contain any additional values in the target field.

IDM3709 The test or validation data cannot be accessed in Naive Bayes test or training.

IDM3739 Gains charts cannot be computed because the data contains less than two target values.

IDM3740 The training data is read.

IDM3741 The Naive Bayes model is built.

IDM3742 The Naive Bayes model is created.

IDM3743 The Naive Bayes classification training process finished.

Explanation

Neural Classification requires a discrete data type.

IDM4441 The predicted field is not numeric.

Explanation

Neural Regression requires a numeric data type.

IDM4442 The categorical field "%1" has "%2" different values.

Explanation

Without automatic normalization at most two different values are allowed.

User response

Use automatic normalization for your input data, or clean the input data source to remove extraneous values.

IDM4443 The argument "%1" for the power option "-errorWeight" is not a valid weight. Error weights must be numbers greater than zero.

IDM4445 Power option for outlier treatment "%1" does not have a valid argument. Arguments may be "ValidValues", "MinMax", or "MissingValues". The option will be ignored.

IDM4446 The prediction field with name "%1" is not contained in the input table. Add this field to the corresponding data object.

IDM4447 The input table for training does not contain the class field "%1". Specify a different name for the class field.

IDM4449 There are not enough valid values in the class field. Check the class field in the input table.

IDM4450 There are not enough valid values in the prediction field. Check the field in the input table.

IDM4451 There are too many different categorical input values, the size of the neural network is too big. Check if there are key fields in the data input.

IDM4452 There are too many different values in field "%1". This field will be ignored for training.

IDM4470 The model cannot be loaded. The required tag "%1" is missing in the model.

Explanation

An XML tag that is specified as mandatory in the relevant PMML is missing. Without this tag, a complete model cannot be constructed.

User response

Recreate the model. If the problem persists, ask the provider of the PMML model for a valid version.

IDM4471 An internal error has occurred.

User response

Try again. If the problem persists and you can reproduce the error, contact your IBM representative.

IDM4472 There is not enough free memory available to complete the requested operation.

IDM7205 The statistics object is not original.

IDM7206 The statistics object does not exist.

IDM7207 The statistics object is not valid.

IDM7210 The parameter file is not valid.

IDM7212 The currently selected method requires that you specify at least two input fields.

Explanation

You might have selected only one input field, or the values in the other input fields are constant.

User response

Specify more input fields, and make sure that these fields do not contain constant values. Then rerun the function again.

IDM7213 The number of records is too small to obtain a result that is statistically valid. Select more input records or reduce the number of input fields. Then run the function again.

IDM7214 This method requires numeric input fields. You cannot use categorical fields. Specify only numeric input fields and rerun the function.

IDM7217 The specified value is not valid for the parameter.

IDM7219 There is not enough main storage on the server to run the function. Stop one or more of the processes that are currently running on the server and restart the function. If the problem persists, and you have other servers at your disposal, try running the function on another server.

IDM7220 The function cannot calculate an appropriate solution because the selected input fields contain unsuitable data. That is, the function, cannot calculate a solution based on real numbers. Try to find out the input fields that might cause this problem. Unselect those input fields and rerun the function.

IDM7223 The input data contains missing values. The function that you want to run does not accept missing values or it does not accept as many missing values.

IDM7224 The specified statistical function is not implemented yet.

IDM7225 The number of parameters transferred to the server is not correct.

Explanation

The client server protocol does not work.

IDM7226 The specified analysis method does not exist.

Explanation

The client server protocol does not work or the data are corrupted.

IDM7227 The input fields "%1" are ignored because the values are constant. The input fields "%2" are ignored because they do not contain enough valid observations. Do not specify these fields for a subsequent mining run because doing so slows down the performance and has no effect on the model building process.

IDM7228 The input fields "%1" contain missing values.

IDM7229 There are not enough valid observation pairs in the input field "%1". The field is ignored. Do not specify this field for a subsequent mining run because doing so slows down the performance and has no effect on the model building process.

IDM7230 The input fields "%1" will be ignored because they do not contain enough valid observations. Do not specify these fields for a subsequent mining run because doing so slows down the performance and has no effect on the model building process.

IDM7231 The input field "%1" is ignored because it contains constant values. Do not specify this field for a subsequent mining run because doing so slows down the performance and has no effect on the model building process.

IDM7234 The maximum lag must be an integer greater than zero.

IDM7236 The settings object does not correspond to cross correlation analysis.

IDM7237 The first variable is not part of the input data for cross correlation.

User response

Please check name of the first variable and the members of your input data.

IDM7238 The second variable is not part of the input data for cross correlation.

User response

Please check name of the second variable and the members of your input data.

IDM7239 The order fields are not part of the input data for cross correlation.

User response

Please check name of the order fields and the members of your input data.

IDM7241 The Intelligent Miner cannot handle the value that you specified for the autocorrelation lag. Specify a value in the range from 1 to less than a quarter of the number of observations.

IDM7242 The confidence interval level must be a number in the range from 0.5 to 0.9999. Specify another confidence interval.

IDM7243 The confidence interval can not be calculated because the input data is unsuitable. Try to find out the fields that have caused this error, and do not not specify them for a subsequent mining run.

IDM7244 To run the Linear Regression function in application mode, you must specify an output data object.

IDM7245 The specified result object "%1" does not exist, or it is not a result object of a Linear Regression analysis. Specify an appropriate result object.

IDM7246 The settings object does not contain parameters for a Linear Regression analysis. Use an appropriate settings object.

IDM7247 Specify the prediction field, that is, the field or variable whose values you want to predict.

IDM7248 Specify the field or variable whose values are to be fitted.

IDM7249 The name of the field to be fitted field is already used for an output field. Specify a unique name for the field to be fitted.

IDM7264 The order fields that you specified were not found in the input data. Check the names of the order fields and the names of these fields in the input data.

IDM7265 The output fields names that you specified were not found among the names of the input fields.

Not all output parameters were transferred to the server.

User response

Contact your system administrator.

IDM7270 The specified use mode is not supported by the Linear Regression function. Specify another use mode.

IDM7271 The number of observations is not sufficient for a Linear Regression analysis.

User response

Add more observations to the input fields or select other input fields and run the analysis again.

IDM7272 The Linear Regression function is unable to calculate a fitting function for the input data because the selected input fields contain unsuitable data. That is, the function cannot calculate a solution based on real numbers. Try to find out the input fields that might cause this problem. Unselect those input fields and rerun the function.

IDM7273 The chosen confidence level is not appropriate for the selected data. You specified an incorrect confidence level or one or more input fields do not contain enough observations. Specify a different confidence level or deselect the input fields that do not contain enough observations before you rerun the function.

IDM7274 The number of variables used in training mode does not match the number of variables used in application mode.

User response

Specify the same number of variables for both modes.

IDM7275 The input fields "%1" are missing in the result object that was generated in training mode. Do not specify input fields for the application mode that were not used for training.

IDM7276 The input fields "%1" are ignored.

Explanation

They are not part of the result object generated in training mode.

User response

Do not specify input fields for the application mode that were not used for training.

IDM7277 The input fields "%1" are excluded from the regression analysis because their significance values exceed the significance threshold, that is, they are not significant enough.

IDM7278 All of the input fields that represent the independent variables were excluded from the regression analysis because their significance values exceed the significance threshold. Specify a higher significance threshold.

IDM7279 The field representing the dependent variable does not contain enough valid observations.

User response

Add more valid observations to this field and run the analysis again.

IDM7280 The field specified as the dependent variable contains constant values, which means that it is statistcally independent. Consequently, the values of this field cannot be predicted by other variables. Specify another field for the dependent variable.

IDM7281 The number of seasonal periods must be an integer between 2 and 99. Correct the number of seasonal periods.

IDM7282 The number of forecast periods must be greater than or equal to zero. Correct the number of forecast periods.

IDM7284 The seasonal model can not be applied to input data containing zero or negative values.

User response

Define a computed field for the input data object that adds a positive constant to the input values. The value of this constant must be so high that all input values become positive. Then run the function again.

IDM7285 The Univariate Curve Fitting function cannot not fit the input data because the data contains values that are negative or zero.

User response

IDM7286 The field that you selected for Univariate Curve Fitting does not contain enough values for the number of seasonal periods you specified. To calculate a valid equation, the function requires at least three times as many input values as there are seasonal periods. If possible, add values or observations to the field or decrease the number of seasonal periods. Then run this function again.

IDM7287 The settings object contains parameters that are not valid for Univariate Curve Fitting. Specify correct parameters and rerun the function.

To predetermine the number of factors, specify an integer from 1 through the number of variables.

IDM7337 The settings object contains parameters that are unsuitable for a factor analysis. Specify another settings object.

IDM7344 This function does not support the specified mode of operation. You can only run the function in training or application mode. Specify one of these two modes.

Specify a prefix in the "Component field prefix" field.

IDM7362 The input field names are not included in the input data.

User response

Check the names of the specified input fields and the names of the fields in your input data. Specify input-field names that match the names of fields in the input data.

IDM7363 The output field names are not included in the input data for the Principal Component Analysis function.

IDM7500 The following item is missing in the model: "%1".

IDM7501 The output file cannot be opened.

IDM7502 Error while writing to output file.

IDM7503 Internal error: array overflow.

IDM7504 Internal error: Cannot set records.

IDM7505 Internal error.

IDM7506 The file specified does not contain a valid regression model.

IDM7507 The file specified is not a valid XML file.

IDM7508 The specified PMML version is not supported.

User response

Refer to the manual for a list of supported versions.

IDM7509 The value of the PMML tag modelType is invalid.

Explanation

Your model might be damaged.

User response

Recreate the model.

IDM7510 The value for the tag %1: %2 is not supported.

Explanation

Make sure that the model conforms to the specified PMML version.

IDM7511 The model is not a value prediction model but a classification model.

User response

Make sure that you apply this function only to linear or polynomial regression models.

IDM7512 The model is not a classification model but a value prediction model.

User response

Make sure that you apply this function only to logistic regression models.

IDM7513 In this model, the extension 'x-sASMode' is activated. This extension is not supported anymore.

Explanation

The model needs the SAS compatibility mode. This mode is not supported anymore. Starting with SAS EM V9.1., SAS supports PMML.

User response

Export the model to PMML from your SAS EM system.

IDM7514 The model is not found.

User response

Specify a larger time limit in the method DM_setExecTime, or reduce the amount of input data, for example, by sampling.

IDM7557 The specified maximum processing time is too small to use the complete input data. With the current training data, Intelligent Miner needs about %1 minutes to use the complete input data.

User response

Specify a larger time limit in the method DM_setExecTime, or reduce the amount of input data, for example, by sampling.

IDM7558 A cancel request was received during the training run.

Explanation

The training run stops immediately. A model is not created.

IDM7559 More than 50 percent of the input data is not valid for regression analysis.

Explanation

Observations that include target fields with NULL values or numerical independent fields with NULL values cannot be used to build a regression model.

User response

Before you start another mining run, filter out the invalid observations because they slow down the performance and have no effect on the model building process.

IDM8400 The Intelligent Miner detected an incorrect parameter %1. Please make sure that the parameter names are specified correctly.

IDM8402 Error while opening file %1.(%2)

IDM8403 The result object %2 has the wrong format or structure. Therefore, a tree model '%1' could not be found. Specify another result object or regenerate a result object containing the desired model.

IDM8404 Error while reading classification tree (%1). The structure of the result object is incorrect. The result object cannot be used.

IDM8405 The Intelligent Miner detected an unknown attribute %1 because the result object does not match the specifications in settings object. Specify a suitable result object for settings object.(%2)

IDM8406 The data type (%1) of a field in the result object does not match the data type (%2) of the corresponding field in the input data object.

IDM8408 The format of the specified result object is obsolete. Generate a new result object in training mode first.

IDM8409 The result object is not valid because the model that it contains (%1) could not be identified as being a pruned tree or an unpruned tree.

IDM8411 Error: getArgs() failure.

IDM8413 The name of the specified pruning algorithm '%1' is incorrect. Check whether you typed the name of the pruning algorithm correctly.

IDM8414 The name of the specified splitting algorithm '%1' is incorrect. Check whether you typed the name of the splitting algorithm correctly.

IDM8415 The name of the specified subsetting algorithm '%1' is incorrect. Check whether you typed the name of the subsetting algorithm correctly.

IDM8416 The tree classifier found an unexpected end to an attribute list.

IDM8417 The tree classifier found a node that had children but no core. The tree will be truncated at this node.

IDM8418 The tree classifier was not able to create a probe array. Therefore, the last split could not be performed.

IDM8419 Warning: a probe lookup failed. The tree classifier had to truncate a node.

IDM8420 An expand operation failed in the tree classifier. The tree classifier was unable to grow the decision tree.

IDM8421 An updating of labels failed in the tree classifier. The Intelligent Miner cannot grow the decision tree.

IDM8430 The tree classifier cannot sort a data array with fewer than zero elements.

IDM8450 No classification label was found in the parameter file.

IDM8451 The Intelligent Miner could not read any records from the input data. Check whether the file containing the input data is empty or if you are authorised to read the file.

IDM8452 The input data contains only 1 class label (%1). A tree model could thus not be generated.

IDM8453 The input field %1 has been ignored because it contains %2 different values in %3 records. The values are too diverse to be useful to classify.

IDM8454 The Intelligent Miner could not read any records from the input data. Check whether the file containing the input data is empty or if all the records lack a class label.

IDM8455 The Intelligent Miner did not calculate distributions because the input fields contain more different categorical values (%1) than are permitted by the threshold value (%2). The threshold value prevents that you run out of memory.

IDM8500 Error while building classification tree.

User response

Check whether the hard drive has enough free space, whetheryou have the proper authorisation to write on the hard drive, and whetherthe specified directory exists.

IDM8509 The Intelligent Miner is unable to read the temporary file %1 (%2). Check whether you have accidentally deleted the temporary file or if your hardware is defective. If neither does apply, contact your IBM representative.

IDM8511 Unable to obtain a temporary file name.(%1)

IDM8512 The Intelligent Miner is unable to create file %1 for the attributes %3 in accordance with the specifications for your operating system %2.(%4)

IDM8514 The Intelligent Miner is unable to create file %1 for the attributes %3 in accordance with the specifications for your operating system %2.(%4)

IDM8515 The Intelligent Miner is unable to write data to file %1. Check whether you have enough disk space.

IDM8516 The Intelligent Miner is unable to write data to file %1. Check whether you have enough disk space.(%2)

IDM8518 The Intelligent Miner is unable to perform a tree classification because of an error in writing a file.

User response

Make sure that there is enough free storage on the file system and that the Intelligent Miner has permission to write files.

IDM8519 The test results could not be merged into the tree classification training model. One of the two XML strings seems to contain a syntax error.

Explanation

This error message is issued by the tree classifier when it tries to incorporate the results of a validation run into a training model.

User response

Make sure that both the training model and the validation model are valid tree models according to the PMML standard.

IDM8601 The calculation of the distributions requires more memory than expected. The memory allocated for is %1 MB. However, the Intelligent Miner will try to use %2 MB.

IDM8620 The process has reached the maximum number of gains charts permitted. Therefore, the Intelligent Miner creates only %1 of the %2 gains charts that would normally have been written.

IDM8621 You have run out of memory. Gains charts were not produced.(%1)

IDM8622 You have run out of memory. Some gain charts may not have been produced.(%1)

IDM8623 Node %1 could not process any data records. The Tree Classification function has stopped.

IDM8640 Usage: %1 input-resultfile output-resultfile

IDM8641 Loading of pruned tree failed (line %1)

IDM8642 Dummy node without a parent detected.

IDM8643 Dummy node whose parent does not have a left child detected.

IDM8644 Boolean operator %1 detected not supported with %2 tag.

IDM8645 Node without predicate detected.

IDM8646 Node with continuous test feature (%1) with more than one %2 detected.

IDM8647 Node with continuous test feature (%1) with unsupported operator %2 detected.

IDM8648 Node with continuous test feature (%1): number expected, but "%2" found.

IDM8649 Node with different categorical test features (%1, %2) detected.

IDM8650 Node with categorical test feature (%1) with unsupported operator %2 detected.

IDM8651 Model used and record to be classified do not match.

IDM8652 More than one class label specified.

IDM8653 Node is not an element node.

IDM8654 Tree model node without score is not feasible.

IDM8655 Node does not have distribution specified.

IDM8656 Invalid node detected: node must not have one single child.

IDM8657 Attribute %1 must not be %2.

IDM8658 %1 is not an attribute of element %2.

IDM8659 No class label specified.

IDM8660 Error reading tree classification model.

IDM8661 The Predicate field %1 is not specified as a MiningField.

IDM8662 The Predicate field %1 of unsupported type is detected.

IDM8663 The Predicate field %1 is continuous, but the value (%2) is non-numeric.

IDM8664 The MiningField name=%1 does not occur in the DataDictionary.

IDM8665 The Predicate name=%1 is not a MiningField.

IDM8666 The Intelligent Miner does not support regression tree scoring.

IDM8667 A cancel request has been received during the tree classification run. The tree classification run will terminate immediately. No model will be written.

IDM8668 This is not an IBM model. The tree classification test mode is only applicable to PMML 2.0 models from IBM.

IDM8669 This is not a PMML 2.0 model. The tree classification test mode is only applicable to PMML 2.0 models from IBM.

IDM8670 The ordinal Predicate field %1 has not defined an order for value %2.

IDM8671 The continuous field %1 must not occur in a SimpleSetPredicate.

IDM8672 The SimpleSetPredicate of field %1 does not have an element "Array".

IDM8673 The attribute %2 of element %1 has a value of %3. This value is not supported.

IDM8674 The model that is used is inconsistent. The model has specified the TreeModel attribute x-normalizationMethod="defaultChild", however, at least one node has not specified x-defaultChild value.

IDM8675 The model that you are using is inconsistent. The model contains the ScoreDistribution attribute x-confidence, however, in at least one node this attribute is missing.

IDM8808 An internal error occurred. The database did not hand in a valid BLOB.

IDM8901 The model is not a Clustering model.

Explanation

The model that was specified as input for a DM_applyClusModel or DM_impClusFile function is not a Clustering model.

IDM8902 The model is not a Classification model.

Explanation

The model that was specified as input for a DM_applyClasModel or DM_impClasFile function is not a Classification model.

IDM8903 The model is not a Regression model.

Explanation

The model that was specified as input for a DM_applyRegModel or DM_impRegFile function is not a Regression model.

IDM8905 Internal error. The type of model is unknown.

Explanation

The model is not recognized as a Clustering, Classification, or Regression model. This is an internal error.

IDM8909 The tree classification test model cannot be applied. Use a tree classification training model instead.

Explanation

Tree Classification test models are used to verify the quality of a training run. You cannot use them for scoring.

User response

Use the Tree Classification training model instead.

IDM8910 The model is not a rule model.

IDM8911 PMML version %1 is not supported.

IDM8914 The header of the model is not valid.

The XML model you want to import does not contain any XML declaration. Therefore the encoding of the model cannot be determined.

User response

You can add an XML declaration at the beginning of the model, or you can specify an encoding when you import the model.

IDM8919 The model (%1 bytes) cannot be stored in a LOB (%2 bytes).

Explanation

After internal conversions, the imported model is too big to be stored in a Large Object (LOB).

User response

You must increase the maximum value for a LOB.

IDM8920 Insufficient memory available to convert and store the model.

User response

Reconnect to the database and try again. If the problem persists, restart the DB2 instance.

IDM8930 Evaluation period over.

IDM8940 Model caching is only available in fenced mode.

Explanation

The function %1 uses the model caching feature, however, model caching is available in fenced mode only.

User response

If you want to use model caching, you must reenable your database in fenced mode by using the command idmenabledb.

IDM8941 The model alias %1 is identical to the model alias of an existing model.

IDM9013 The parameter name "%1" in the optional parameter string is not known.

Explanation

Reduce the number of distinct values of the stratified sample column by creating a view. In this view, map the values of the stratified sample column to a small number of distinct values.