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Principal Component Analysis in Python

Abhinav Choudhary shows us how to implement Principal Component Analysis in Python:

Principal Component Analysis (PCA) is an unsupervised statistical technique used to examine the interrelation among a set of variables in order to identify the underlying structure of those variables. In simple words, suppose you have 30 features column in a data frame so it will help to reduce the number of features making a new feature which is the combined effect of all the feature of the data frame. It is also known as factor analysis.

PCA is quite useful in practice, though it has the unfortunate side effect of making it harder to interpret which factors are driving your solution.