Machine Learning
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PCA
Quick Definition
Statistical technique reducing dimensionality via principal components
Full Definition
Principal Component Analysis reduces dimensionality by transforming features into uncorrelated principal components.
Examples
data visualization, noise reduction, feature extraction
Related Terms
dimensionality-reduction
feature-extraction
More Machine Learning Terms
Imbalanced Learning
Handling datasets with unequal class distributions
Feature Selection
Identifying the most relevant features for model training
Loss Function
Math function measuring prediction vs actual value difference
Dimensionality Reduction
Reducing feature count while preserving important information
Gradient Boosting
Sequential ensemble method correcting previous model errors
Contrastive Learning
Self-supervised learning by contrasting data pairs