Class Summary |
Attribute |
A class describing an attribute in a machine learning problem: in particular,
the name of the attribute and the values it can take |
AttributeSet |
AttributeSet encapsulates the set of attributes for a given machine learning
problem. |
Classifier |
The Classifier class represents an algorithm for classifying the instances of
a particular machine learning problem. |
DecisionStump |
The DecisionStump class implements a 1-level decision tree |
DecisionTree |
Implements a simple decision tree classifier with no pruning. |
DecisionTreeNode |
A DecisionTreeNode represents a single node in a decision tree. |
NaiveBayes |
The NaiveBayes class implements the naive Bayes classification algorithm
(i.e. |
OneRClassifier |
The OneRClassifier class implements the 1R classification algorithm |