IBM SPSS Modeler Tutorial
- About IBM SPSS Modeler
- Product Overview
- Introduction to Modeling
- Automated Modeling for a Flag Target
- Automated Modeling for a Continuous Target
- Automated Data Preparation (ADP)
- Preparing Data for Analysis (Data Audit)
- Drug Treatments (Exploratory Graphs/C5.0)
- Screening Predictors (Feature Selection)
- Reducing Input Data String Length (Reclassify Node)
- Modeling Customer Response (Decision List)
- Classifying Telecommunications Customers (Multinomial Logistic Regression)
- Telecommunications Churn (Binomial Logistic Regression)
- Forecasting Bandwidth Utilization (Time Series)
- Forecasting Catalog Sales (Time Series)
- Making Offers to Customers (Self-Learning)
- Predicting Loan Defaulters (Bayesian Network)
- Retraining a Model on a Monthly Basis (Bayesian Network)
- Retail Sales Promotion (Neural Net/C&RT)
- Condition Monitoring (Neural Net/C5.0)
- Classifying Telecommunications Customers (Discriminant Analysis)
- Analyzing Interval-Censored Survival Data (Generalized Linear Models)
- Using Poisson Regression to Analyze Ship Damage Rates (Generalized Linear Models)
- Fitting a Gamma Regression to Car Insurance Claims (Generalized Linear Models)
- Classifying Cell Samples (SVM)
- Using Cox Regression to Model Customer Time to Churn
- Market Basket Analysis (Rule Induction/C5.0)
- Assessing New Vehicle Offerings (KNN)
- Uncovering causal relationships in business metrics (TCM)
- Glossary