supervisedAttributeScaling: A simple filter to rescale attributes to reflect their discriminative power.

URL:http://weka.sourceforge.net/doc.packages/supervisedAttributeScaling
Author:Eibe Frank
Maintainer:Weka team <wekalist{[at]}list.scms.waikato.ac.nz>

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.

All available versions:
Latest
1.0.0