A new feature selection approach for optimizing prediction models, applied to breast cancer subtype classification
Feature selection is a useful technique in classification (and regression) problems to find the most informative features for predicting but still preserves the data generality. However, some feature subset searching methods are too exhaustive while others are too greedy. On the other hand, paramete...
Saved in:
Main Authors: | Phạm, Quang Huy, Alioune Ngom, Luis Rueda |
---|---|
Format: | Conference poster |
Language: | English |
Published: |
IEEE
2023
|
Subjects: | |
Online Access: | https://scholar.dlu.edu.vn/handle/123456789/2711 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institutions: | Thư viện Trường Đại học Đà Lạt |
---|
Similar Items
-
A Novel Approach for Identifying Relevant Genes for Breast Cancer Survivability on Specific Therapies
by: Tabl, Ashraf Abou, et al.
Published: (2023) -
Machine Learning Approaches for Breast Cancer Survivability Prediction
by: Phạm, Quang Huy
Published: (2023) -
A novel approach for identifying relevant genes for breast cancer survivability on specific therapies
by: Phạm, Quang Huy, et al.
Published: (2023) -
Estimation and feature selection in high-dimensional mixtures-of-experts models
by: Huỳnh, Bảo Tuyên
Published: (2023) -
A Data Integration Approach for Detecting Biomarkers of Breast Cancer Survivability
by: Phạm, Quang Huy, et al.
Published: (2023)