SVM for regression

As for regression, the SVM algorithms presented by scikit-learn are shown here:





The LIBSVM implementation for regression

C, kernel, degree, gamma, and epsilon


Same as for .SVR

nu, C, kernel, degree, and gamma

To provide an example of regression, we decided on a dataset of real estate prices of houses in California (a slightly different problem than the previously seen Boston housing prices dataset):

In: import pickle    X_train, y_train = pickle.load(open( "cadata.pickle", "rb" ))    from sklearn.preprocessing import scale    first_rows = 2000    X_train = scale(X_train[:first_rows,:].toarray())    y_train = y_train[:first_rows]/10**4.0 

The cases ...

Get Python Data Science Essentials - Third Edition now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.