nz.ac.waikato.cms.weka : supervisedAttributeScaling

supervisedAttributeScaling · Package containing a class that rescales the attributes in a classification problem based on their discriminative power. This is useful as a pre-processing step for learning algorithms such as the k-nearest-neighbour method, to replace simple normalization. Each attribute is rescaled by multiplying it with a learned weight. All attributes excluding the class are assumed to be numeric and missing values are not permitted. To achieve the rescaling, this package also contains an implementation of non-negative logistic regression, which produces a logistic regression model with non-negative weights .

javadoc --ignore-source-errors -encoding UTF-8 -sourcepath "supervisedAttributeScaling-1.0.2-sources.jar" -d "supervisedAttributeScaling-1.0.2-javadoc" -subpackages