Machine Learning
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Feature Selection
Quick Definition
Identifying the most relevant features for model training
Full Definition
Identifying the most relevant features from a dataset for use in model training.
Examples
recursive feature elimination, mutual information, L1 regularization
Related Terms
feature-engineering
dimensionality-reduction
More Machine Learning Terms
Cross-Validation
Evaluating model performance with multiple data splits
Gradient Descent
Optimization algorithm minimizing loss by steepest descent
Kernel Trick
Transforming data to higher dimensions for linear separability
Dropout
Regularization randomly deactivating neurons during training
Data Augmentation
Artificially increasing training data through modified copies
t-SNE
Nonlinear technique for visualizing high-dimensional data