Uses of Class
weka.filters.SimpleBatchFilter
Package
Description
-
Uses of SimpleBatchFilter in weka.filters.supervised.attribute
Modifier and TypeClassDescriptionclass
A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.class
Converts the values of nominal and/or numeric attributes into class conditional probabilities.class
Merges values of all nominal attributes among the specified attributes, excluding the class attribute, using the CHAID method, but without considering re-splitting of merged subsets. -
Uses of SimpleBatchFilter in weka.filters.supervised.instance
Modifier and TypeClassDescriptionclass
Reweights the instances in the data so that each class has the same total weight. -
Uses of SimpleBatchFilter in weka.filters.unsupervised.attribute
Modifier and TypeClassDescriptionclass
A filter for performing the Cartesian product of a set of nominal attributes.class
A filter for turning date attributes into numeric ones.class
A filter for detecting outliers and extreme values based on interquartile ranges.class
Converts the given set of data into a kernel matrix.class
Merges all values of the specified nominal attributes that are insufficiently frequent.class
A filter for turning numeric attributes into date attributes.class
A filter for turning numeric attributes into nominal ones.class
A filter that applies filters on subsets of attributes and assembles the output into a new dataset.class
Chooses a random subset of non-class attributes, either an absolute number or a percentage.class
A filter that can be used to introduce missing values in a dataset.class
Transposes the data: instances become attributes and attributes become instances. -
Uses of SimpleBatchFilter in weka.filters.unsupervised.instance
Modifier and TypeClassDescriptionclass
Removes all duplicate instances from the first batch of data it receives.class
Filters instances according to a user-specified expression.
Examples:
- extracting only mammals and birds from the 'zoo' UCI dataset:
(CLASS is 'mammal') or (CLASS is 'bird')
- extracting only animals with at least 2 legs from the 'zoo' UCI dataset:
(ATT14 >= 2)
- extracting only instances with non-missing 'wage-increase-second-year'
from the 'labor' UCI dataset:
not ismissing(ATT3)