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Binarsity: a penalization for one-hot encoded features in linear
  supervised learning
v1v2v3v4 (latest)

Binarsity: a penalization for one-hot encoded features in linear supervised learning

24 March 2017
Mokhtar Z. Alaya
Simon Bussy
Stéphane Gaïffas
Agathe Guilloux
ArXiv (abs)PDFHTML

Papers citing "Binarsity: a penalization for one-hot encoded features in linear supervised learning"

5 / 5 papers shown
Title
Deep Configuration Performance Learning: A Systematic Survey and
  Taxonomy
Deep Configuration Performance Learning: A Systematic Survey and Taxonomy
Jingzhi Gong
Tao Chen
BDL
57
5
0
05 Mar 2024
Estimation of an Order Book Dependent Hawkes Process for Large Datasets
Estimation of an Order Book Dependent Hawkes Process for Large Datasets
Luca Mucciante
Alessio Sancetta
15
4
0
18 Jul 2023
Does Configuration Encoding Matter in Learning Software Performance? An
  Empirical Study on Encoding Schemes
Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes
Jing Gong
Tao Chen
61
14
0
30 Mar 2022
Modeling High-Dimensional Data with Unknown Cut Points: A Fusion
  Penalized Logistic Threshold Regression
Modeling High-Dimensional Data with Unknown Cut Points: A Fusion Penalized Logistic Threshold Regression
Yi-Qi Lin
Wen-Xin Zhou
Zhi Geng
G. Xiao
Jianxin Yin
51
0
0
17 Feb 2022
Binacox: automatic cut-point detection in high-dimensional Cox model
  with applications in genetics
Binacox: automatic cut-point detection in high-dimensional Cox model with applications in genetics
Simon Bussy
Mokhtar Z. Alaya
A. Jannot
Agathe Guilloux
47
0
0
25 Jul 2018
1