sklearn.decomposition 中的 PCA 中的 fit、transform 和 fit_transform 有什么作用？

Question

I am trying to mimic the behavior of PCA class available in sklearn.decomposition .

I have wrote a method which computes the SVD but I am not sure what does fit() , tranform() , and fit_transform() do without which I'm not able to proceed further.

I think fit() computes the svd and the singular values can be accessed using the singular_values_ attribute but I don't know about the remaining two methods.

Answer 1

In the docs you can see a general explanation of fit() , transform() , and fit_transform() :

[...] a fit method, which learns model parameters (eg mean and standard deviation for normalization) from a training set, and a transform method which applies this transformation model to unseen data. fit_transform may be more convenient and efficient for modelling and transforming the training data simultaneously.