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
Semi-Supervised Learning
Combining small labeled datasets with large unlabeled data
Underfitting
When a model is too simple to capture data patterns
Logistic Regression
Statistical model estimating binary outcome probabilities
Loss Function
Math function measuring prediction vs actual value difference
Bias-Variance Tradeoff
The tension between model simplicity and complexity errors
DBSCAN
Density-based clustering finding clusters of varying shapes