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Labwork1 - Machine learning and data mining 2

My findings

  • PCA or Principal Component Analysis is a method to reduce the initial dataset size to a smaller one with fewer independent variables/attributes, and mostly applied in classification problems. For regression, we have PCR or Principal Component Regression.
  • Each principal component is a linear combination of the original variables:
PC = w1X1 + w1X2 + ... + wnXn
where X is the original variable and w is weight/coefficient

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