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| -rw-r--r-- | README.rst | 7 |
1 files changed, 4 insertions, 3 deletions
@@ -32,7 +32,7 @@ If you use this package in your research please cite the paper, for instance using the following BibTeX entry:: @article{JMLR:v17:14-526, - author = {Gerrit J.J. van den Burg and Patrick J.F. Groenen}, + author = {{van den Burg}, G. J. J. and Groenen, P. J. F.}, title = {{GenSVM}: A Generalized Multiclass Support Vector Machine}, journal = {Journal of Machine Learning Research}, year = {2016}, @@ -61,10 +61,11 @@ from Scikit-Learn as follows: >>> from sklearn.datasets import load_iris >>> from sklearn.model_selection import train_test_split - >>> from sklearn.preprocessing import maxabs_scale + >>> from sklearn.preprocessing import MaxAbsScaler >>> X, y = load_iris(return_X_y=True) - >>> X = maxabs_scale(X) >>> X_train, X_test, y_train, y_test = train_test_split(X, y) + >>> scaler = MaxAbsScaler().fit(X_train) + >>> X_train, X_test = scaler.transform(X_train), scaler.transform(X_test) Note that we scale the data using the `maxabs_scale <http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html>`_ |