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
LightGBM
Fast gradient boosting framework using histogram splitting
Unsupervised Learning
Discovering hidden patterns in unlabeled data
Boosting
Sequentially combining weak learners correcting previous errors
DBSCAN
Density-based clustering finding clusters of varying shapes
Data Augmentation
Artificially increasing training data through modified copies
Margin
Distance between decision boundary and nearest data points