Machine Learning
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Lasso Regression
Quick Definition
Regularized regression using L1 penalty for feature selection
Full Definition
A regularized regression method using L1 penalty that can shrink some coefficients to zero for feature selection.
Examples
feature selection, sparse models, high-dimensional data
Related Terms
ridge-regression
regularization
feature-selection
More Machine Learning Terms
Boosting
Sequentially combining weak learners correcting previous errors
Unsupervised Learning
Discovering hidden patterns in unlabeled data
Regularization
Techniques constraining model complexity to prevent overfitting
Bayesian Optimization
Optimizing expensive functions using a probabilistic model
Model Selection
Choosing the best ML model from candidates
Survival Analysis
Statistical methods analyzing time until an event occurs