Uses of Interface
weka.core.Summarizable

Packages that use Summarizable

weka.classifiers
weka.classifiers.meta
weka.classifiers.rules
weka.classifiers.trees

Uses of Summarizable in weka.classifiers

Classes in weka.classifiers that implement Summarizable

class

Evaluation Class for evaluating machine learning models.

Uses of Summarizable in weka.classifiers.meta

Classes in weka.classifiers.meta that implement Summarizable

class	CVParameterSelection Class for performing parameter selection by cross-validation for any classifier. For more information, see: R.
class	GridSearch Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) and the PLSFilter (X-axis, "# of Components") and chooses the best pair found for the actual predicting. The initial grid is worked on with 2-fold CV to determine the values of the parameter pairs for the selected type of evaluation (e.g., accuracy).

Uses of Summarizable in weka.classifiers.rules

Classes in weka.classifiers.rules that implement Summarizable

class

PART Class for generating a PART decision list.

Uses of Summarizable in weka.classifiers.trees

Classes in weka.classifiers.trees that implement Summarizable

class	J48 Class for generating a pruned or unpruned C4.5 decision tree.
class	J48graft Class for generating a grafted (pruned or unpruned) C4.5 decision tree.
class	NBTree Class for generating a decision tree with naive Bayes classifiers at the leaves. For more information, see Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid.