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Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences
Daniel M. McNeish
Research output
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Contribution to journal
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Article
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peer-review
225
Scopus citations
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Dive into the research topics of 'Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences'. Together they form a unique fingerprint.
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Mathematics
Overfitting
94%
Lasso
82%
Predictors
64%
Regression Coefficient
28%
Parsimony
19%
Ridge Regression
17%
Ordinary Least Squares
16%
Standard Model
15%
p-Value
15%
Regularization Method
14%
Standard error
14%
Statistical Model
13%
Software
12%
Continue
12%
Regularization
12%
Model
4%
Arts & Humanities
Behavioral Science
88%
Predictors
75%
Parsimony
15%
Statistical Model
12%
Invisible
10%
Medicine & Life Sciences
Behavioral Sciences
100%
Science in Literature
21%
Behavioral Research
16%
Statistical Models
13%
Least-Squares Analysis
13%
Software
8%
Social Sciences
behavioral science
78%
regression
22%
software
8%
literature
4%