Sources & Features etc.

[dmpe]

https://github.com/jakevdp/sklearn_pycon2015/blob/master/notebooks/03.1-Classification-SVMs.ipynb

[dmpe]

https://github.com/paper82/pylometry/tree/master/features < All in python

[dmpe]

http://ftp.cs.toronto.edu/pub/gh/Feng-thesis-2015.pdf

[dmpe]

http://scikit-learn.org/stable/auto_examples/hetero_feature_union.html http://scikit-learn.org/stable/modules/pipeline.html#feature-union (http://scikit-learn.org/stable/modules/generated/sklearn.pipeline.FeatureUnion.html#sklearn.pipeline.FeatureUnion)

We use the 20-newsgroups dataset and compute standard bag-of-words features for the subject line and body in separate pipelines as well as ad hoc features on the body. We combine them (with weights) using a FeatureUnion and finally train a classifier on the combined set of features.

[dmpe]

http://zacstewart.com/2014/08/05/pipelines-of-featureunions-of-pipelines.html <> https://stackoverflow.com/questions/25250654/how-can-i-use-a-custom-feature-selection-function-in-scikit-learns-pipeline https://github.com/scikit-learn/scikit-learn/issues/2034

[dmpe]

http://users.sussex.ac.uk/~christ/crs/ml/lec03a.html

[dmpe]

http://scikit-learn.org/stable/auto_examples/model_selection/grid_search_digits.html#example-model-selection-grid-search-digits-py http://scikit-learn.org/stable/auto_examples/neural_networks/plot_rbm_logistic_classification.html http://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html https://www.quantstart.com/articles/Using-Cross-Validation-to-Optimise-a-Machine-Learning-Method-The-Regression-Setting http://scikit-learn.org/stable/auto_examples/feature_selection/plot_permutation_test_for_classification.html