A Statistical-Mining Techniques’ Collaboration for Minimizing Dimensionality in Ovarian Cancer Data

A feature is a single measurable criterion to an observation of process. While knowledge discovery techniques successfully contribute many fields, however, the extensive required data processing could hinder performance these techniques. One main issues in dimensionality data. Therefore, focusing on reducing through eliminating insignificant attributes be considered one successful steps for raising applied techniques’ performance. On other hand, field, ovarian cancer patients continuously suffer from analysis requirements detecting disease as well monitoring treatment progress. identifying most significant positive step reduce emotional and financial suffering. This research aims highlight using collaboration clustering statistical The succeeded identify twelve out forty-four with total fourteen