16 results
- Go to itemClass for generating a pruned or unpruned C4.5 decision tree. For more information, see Ross Quinlan (1993). C4.5: Programs for M…0
- Go to itemClass for generating a grafted (pruned or unpruned) C4.5 decision tree. For more information, see Geoff Webb: Decision Tree Graft…0
- Go to itemClass for generating a multi-class alternating decision tree using the LogitBoost strategy. For more info, see Geoffrey Holmes, B…0
- Go to itemClassifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves. …0
- Go to itemM5Base. Implements base routines for generating M5 Model trees and rules The original algorithm M5 was invented by R. Quinlan and…0
- Go to itemClass for generating a decision tree with naive Bayes classifiers at the leaves. For more information, see Ron Kohavi: Scaling Up…0
- Go to itemClass for generating an alternating decision tree. The basic algorithm is based on: Freund, Y., Mason, L.: The alternating decisi…0
- Go to itemClass for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. F…0
- Go to itemClass for building and using a decision stump. Usually used in conjunction with a boosting algorithm. Does regression (based on m…0
- Go to itemClassifier for building 'Functional trees', which are classification trees that could have logistic regression functions at the i…0
- Go to itemClass for constructing an unpruned decision tree based on the ID3 algorithm. Can only deal with nominal attributes. No missing va…0
- Go to itemClass for constructing a random forest*. (based on WEKA 3.6) For further options, click the 'More' - button in the dialog. All we…0
- Go to itemClass for constructing a tree that considers K randomly chosen attributes at each node. Performs no pruning. Also has an option t…0
- Go to itemFast decision tree learner. Builds a decision/regression tree using information gain/variance and prunes it using reduced-error p…0
- Go to itemClass implementing minimal cost-complexity pruning. Note when dealing with missing values, use "fractional instances" method inst…0
- Go to itemInteractively classify through visual means. You are Presented with a scatter graph of the data against two user selectable attri…0