Correlation-based feature selection of single cell transcriptomics data from multiple sources

Correlation-based feature selection of single cell transcriptomics data from multiple sources

Abstract When applying data mining or machine learning techniques to large and diverse datasets, it is often necessary to construct descriptive and predictive models. Descriptive models are used to discover relationships between the attributes of the data while predictive models identify the charact...

Full description

Saved in:
Bibliographic Details
Main Authors: Nenad S. Mitić, Saša N. Malkov, Mirjana M. Maljković Ružičić, Aleksandar N. Veljković, Ivan Lj. Čukić, Xin Lin, Minjie Lyu, Vladimir Brusić
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Journal of Big Data
Subjects:
Feature selection
High-dimensional data
Classification
Transcriptomics data
Online Access:https://doi.org/10.1186/s40537-024-01051-z
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s40537-024-01051-z

Similar Items