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Package

weka.filters.unsupervised.attribute

Synopsis

An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. Discretization is by simple binning. Skips the class attribute if set.

Options

The table below describes the options available for Discretize.

Option

Description

attributeIndices

Specify range of attributes to act on. This is a comma separated list of attribute indices, with "first" and "last" valid values. Specify an inclusive range with "-". E.g: "first-3,5,6-10,last".

bins

Number of bins.

desiredWeightOfInstancesPerInterval

Sets the desired weight of instances per interval for equal-frequency binning.

findNumBins

Optimize number of equal-width bins using leave-one-out. Doesn't work for equal-frequency binning

ignoreClass

The class index will be unset temporarily before the filter is applied.

invertSelection

Set attribute selection mode. If false, only selected (numeric) attributes in the range will be discretized; if true, only non-selected attributes will be discretized.

makeBinary

Make resulting attributes binary.

useEqualFrequency

If set to true, equal-frequency binning will be used instead of equal-width binning.

Capabilities

The table below describes the capabilites of Discretize.

Capability

Supported

Class

String class, Binary class, Relational class, Missing class values, Date class, Empty nominal class, No class, Numeric class, Nominal class, Unary class

Attributes

Nominal attributes, Numeric attributes, Missing values, Relational attributes, Empty nominal attributes, Unary attributes, Date attributes, String attributes, Binary attributes

Min # of instances

0

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