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L0-Constrained Regression for Data Mining
Zhili Wu
*
, Chun-hung Li
*
Corresponding author for this work
Department of Computer Science
Research output
:
Chapter in book/report/conference proceeding
›
Conference proceeding
›
peer-review
7
Citations (Scopus)
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Dive into the research topics of 'L0-Constrained Regression for Data Mining'. Together they form a unique fingerprint.
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Mathematics
Minimizes
100%
Data Mining
100%
Compact Set
100%
Regression Coefficient
100%
Nonlinear Regression
100%
Ridge Regression
100%
Least Absolute Shrinkage and Selection Operator
100%
Computer Science
Data Mining
100%
Regression Method
100%
Feature Selection
50%
Feature Extraction
50%
Regression Coefficient
50%
Ridge Regression
50%
Nonlinear Regression
50%
Fitting Coefficient
50%
Engineering
Least Absolute Shrinkage and Selection Operator
100%
Feature Extraction
100%
Nonlinear Regression
100%
Compact Set
100%
Regression Coefficient
100%
Keyphrases
Constrained Regression
100%
Regression Method
40%
Fitting Error
40%
Least Absolute Shrinkage and Selection Operator (LASSO)
20%
Feature Selection
20%
Regression Coefficient
20%
Feature Classifier
20%
Nonlinear Regression
20%
Compact Set
20%
Ridge Regression
20%
Linearization Algorithm
20%
ℓ0 Constraint
20%
Successive Linearization Method
20%
Constraint Classification
20%
Classifier Constructions
20%
Fitting Ability
20%
Error Constraint
20%
Fitting Coefficient
20%