Technical Information

• DTREG training tutorials

• Benchmark results for different models
• Time series analysis and forecasting
• How trees are built
• How trees are pruned
• TreeBoost - Stochastic gradient boosting
• Decision Tree Forests - Ensembles of trees
• Multilayer Perceptron Neural Network models
• RBF Neural Network models
• GMDH Polynomial Neural Networks
• Cascade Correlation Neural Network models
• Probabilistic and General Regression Neural Network models
• Support Vector Machine (SVM) models
• Gene Expression Programming - Symbolic Regression models
• Linear Discriminant Analysis (LDA) models
• Linear Regression models
• Logistic Regression models
• Lift and Gain tables and charts
• V-fold cross validation
• Missing values, surrogate variables, and surrogate splitters
• DTREG .NET Class Library

• Main screen
• Tree view screen
• Model parameters
• TreeBoost parameters
• Decision Tree Forest parameters
• Multilayer Perceptron Neural Network parameters
• RBF Neural Network parameters
• Probabilistic and General Regression Neural Network parameters
• Cascade Correlation Neural Network parameters
• Support Vector Machine parameters
• Model variables
• Model variable weights
• Model cross-validation and pruning
• Model misclassification costs
• Model prior probabilities
• Model forced initial split
• Scoring data values
• Pagenated tree that crosses pages
• Gain chart
• Model size/Error rate chart
• Variable importance chart
• Probability threshold chart
• Receiver Operating Characteristic (ROC) chart
• Probability Calibration chart

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