Package weka.attributeSelection

package weka.attributeSelection
  • Class
    Description
    ASEvaluation
    Abstract attribute selection evaluation class
    ASSearch
    Abstract attribute selection search class.
    AttributeEvaluator
    Interface for classes that evaluate attributes individually.
    AttributeSelection
    Attribute selection class.
    AttributeSetEvaluator
    Abstract attribute set evaluator.
    AttributeTransformer
    Abstract attribute transformer.
    BestFirst
    BestFirst:

    Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
    CfsSubsetEval
    CfsSubsetEval :

    Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

    Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

    For more information see:

    M.
    CheckAttributeSelection
    Class for examining the capabilities and finding problems with attribute selection schemes.
    ClassifierAttributeEval
    ClassifierAttributeEval :

    Evaluates the worth of an attribute by using a user-specified classifier.
    ClassifierSubsetEval
    Classifier subset evaluator:

    Evaluates attribute subsets on training data or a separate hold out testing set.
    CorrelationAttributeEval
    CorrelationAttributeEval :

    Evaluates the worth of an attribute by measuring the correlation (Pearson's) between it and the class.

    Nominal attributes are considered on a value by value basis by treating each value as an indicator.
    ErrorBasedMeritEvaluator
    Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
    GainRatioAttributeEval
    GainRatioAttributeEval :

    Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.

    GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute).
    GreedyStepwise
    GreedyStepwise :

    Performs a greedy forward or backward search through the space of attribute subsets.
    HoldOutSubsetEvaluator
    Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
    InfoGainAttributeEval
    InfoGainAttributeEval :

    Evaluates the worth of an attribute by measuring the information gain with respect to the class.

    InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute).
    OneRAttributeEval
    OneRAttributeEval :

    Evaluates the worth of an attribute by using the OneR classifier.
    PrincipalComponents
    Performs a principal components analysis and transformation of the data.
    RankedOutputSearch
    Interface for search methods capable of producing a ranked list of attributes.
    Ranker
    Ranker :

    Ranks attributes by their individual evaluations.
    ReliefFAttributeEval
    ReliefFAttributeEval :

    Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.
    StartSetHandler
    Interface for search methods capable of doing something sensible given a starting set of attributes.
    SubsetEvaluator
    Interface for attribute subset evaluators.
    SymmetricalUncertAttributeEval
    SymmetricalUncertAttributeEval :

    Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.
    UnsupervisedAttributeEvaluator
    Abstract unsupervised attribute evaluator.
    UnsupervisedSubsetEvaluator
    Abstract unsupervised attribute subset evaluator.
    WrapperSubsetEval
    WrapperSubsetEval:

    Evaluates attribute sets by using a learning scheme.