Machine Learning
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Regularization
Quick Definition
Techniques constraining model complexity to prevent overfitting
Full Definition
Techniques that constrain or penalize model complexity to prevent overfitting and improve generalization.
Examples
L1/L2 regularization, dropout, early stopping
Related Terms
overfitting
lasso
ridge-regression
More Machine Learning Terms
Overfitting
When a model learns training data noise and fails on new data
Autoencoder
Neural network learning compressed data representations
Lasso Regression
Regularized regression using L1 penalty for feature selection
ROC Curve
Plot showing classifier performance across thresholds
Hyperparameter Tuning
Finding optimal configuration values before training
Random Forest
Ensemble of decision trees that votes on predictions