http://www.information-management.com/issues/20060301/1048507-1.html
http://en.wikipedia.org/wiki/Predictive_analytics

CART
CHAID
C4.5
k-Nearest Neighbors
Hierarchical Clustering
Naive Bayes
Decision Trees
BIRCH
CURE
Association Rules
Time Series Analysis: Exponential Smoothing
Time Series Analysis: Box-Jenkins
Linear Regression
Nonlinear Regression
Logistic Regression
Neural networks
Principal Component Analysis
Factor Analysis
Radial Basis Functions
Support Vector Machines

Modeling algorithms in SPSS Modeler

    *  Decision tree algorithms, including interactive tree building (C&RT, C5.0, CHAID & QUEST).
    * An interactive rule-building algorithm (Decision List).
    * Clustering and segmentation algorithms (K-Means, Kohonen, Two Step, Discriminant, Support Vector Machine).
    * Data reduction algorithms (Factor/PCA, Feature Selection).
    * Linear equation modeling (Regression, Linear, GenLin).
    * Bayesian model with incremental learning (self-learning response model).
    * Time-series forecasting models.
    * Neural Networks (multi-layer perceptrons with back-propagation learning, and radial basis function networks).
    * An advanced algorithm for wide datasets (Support Vector Machine).
    * Graphical probabilistic models (Bayesian networks).
    * Calculate the likely time to an event (Cox regression).
    * Cluster-based algorithm for detecting unusual results (anomaly detection).
    * Nearest neighbor modeling and scoring algorithm (KNN).
    * Association discovery algorithm with advanced evaluation functions (Apriori).
    * Association algorithm that supports multiple consequents (CARMA).
    * Sequential association algorithm for order-sensitive analyses (Sequence).