TY  - CHAP
AU  - Calviño Martínez, Aída
AU  - Moreno Ribera, Almudena
AU  - Pineda Sanjuan, Silvia
A4  - Larriba, Yolanda
PY  - 2023
DO  - 10.1007/978-3-031-32729-2_2
SN  - 978-3-031-32728-5
SN  - 978-3-031-32729-2
UR  - https://hdl.handle.net/20.500.14352/91677
AB  - In this chapter we illustrate the use of some Machine Learning techniques in the context of omics data. More precisely, we review and evaluate the use of Random Forest and Penalized Multinomial Logistic Regression for integrative analysis of genomics...
LA  - eng
M2  - 21
PB  - Springer
KW  - Genomics
KW  - High-throughput data
KW  - Association rules
KW  - Random Forest
KW  - LASSO
TI  - Machine learning applied to omics data
TY  - book part
ER  -