Artificial Intelligence based wrapper for high dimensional feature selection.

ABSTRACT:

Background

Feature selection is important in high dimensional data analysis. The wrapper approach is one of the ways to perform feature selection, but it is computationally intensive as it builds and evaluates models of multiple subsets of features. The existing wrapper algorithm primarily focuses on shortening the path to find an optimal feature set. However, it underutilizes the capability of feature subset models, which impacts feature selection and its predictive performance.

Method and results

This study proposes a novel Artificial Intelligence based Wrapper (AIWrap) algorithm that integrates Artificial Intelligence (AI) with the existing wrapper algorithm. The algorithm develops a Performance Prediction Model using AI which predicts the model performance of any feature

SUBMITTER: Jain R 

PROVIDER: S-EPMC10585895 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature