Author:Eibe Frank
Category:Preprocessing
Changes:Improved description of algorithm in global information.
Date:2018-10-30
Depends:weka (>=3.7.6)
Description: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.
License:GPL 3.0
Maintainer:Weka team <wekalist{[at]}list.scms.waikato.ac.nz>
PackageURL:http://prdownloads.sourceforge.net/weka/supervisedAttributeScaling1.0.2.zip?download
URL:http://weka.sourceforge.net/doc.packages/supervisedAttributeScaling
Version:1.0.2