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Unsupervised Learning: Difference between revisions
→Dimension Reduction
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Goal: Find a vector <math>v_1</math> such that the projection <math>v_1 \cdot x</math> has maximum variance.<br> | Goal: Find a vector <math>v_1</math> such that the projection <math>v_1 \cdot x</math> has maximum variance.<br> | ||
These principal components are the eigenvectors of <math>X^TX</math>.<br> | These principal components are the eigenvectors of <math>X^TX</math>.<br> | ||
===Kernel PCA=== | |||
===Autoencoder=== | |||