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 |