ILRC: a hybrid biomarker discovery algorithm based on improved L1 regularization and clustering in microarray data.

ABSTRACT:

Background

Finding significant genes or proteins from gene chip data for disease diagnosis and drug development is an important task. However, the challenge comes from the curse of the data dimension. It is of great significance to use machine learning methods to find important features from the data and build an accurate classification model.

Results

The proposed method has proved superior to the published advanced hybrid feature selection method and traditional feature selection method on different public microarray data sets. In addition, the biomarkers selected using our method show a match to those provided by the cooperative hospital in a set of clinical cleft lip and palate data.

Method

In this paper, a feature selection algorithm ILRC based on clustering and i

SUBMITTER: Yu K 

PROVIDER: S-EPMC8532312 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature