ADTree
The alternating decision tree algorithm uses confidence-rated AdaBoost to build a generalized voted decision tree with a model that is relatively to interpet. Read More...
Decision Tree
The decision tree is a simple, fast learning algorithm that induces a concise graphical model from a set of examples by partitioning the feature space. Read More...
Boosted Weighted Tree
The weighted boosted tree algorithm implements AdaBoost/confidence-rated Adaboost on the decision tree which learns from weighted instances. Read More...
Boosted C45
The boosted C4.5 algorithm implements AdaBoost on the C4.5 decision tree performing weighted sampling. Read More...
LIBSVM
LibSVM is an implementation of Support Vector Machines (SVM) proposed by Vapnik. The SVM classifier performs linear classification finding the maximal margin hyperplane. The "kernel trick" extends SVM to non-linear problems. Read More...
C45
The C4.5 decision tree is a mature tree implementation that can handle a wide range of applications. Read More...