Hello, A few points on the documentation / examples in the scikit-learn site:
* In the example that plots the decision surface of a decision tree on the Iris dataset (http://scikit-learn.org/stable/auto_examples/tree/plot_iris.html#example-tree-plot-iris-py), the dataset is initially shuffled and standardised. Is that necessary? Decision trees do not require data shuffling and standardisation, or am I mistaken? * In the bias-variance decomposition example (http://scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html#example-ensemble-plot-bias-variance-py) it would be nice if the acronym “LS” were explained. Right now I can think of a couple of possibilities of what it might mean exactly. * The FAQ link on the main page (http://scikit-learn.org/stable/faq/) is broken. Thanks for you excellent work and best regards, Panos. ------------------------------------------------------------------------------ Site24x7 APM Insight: Get Deep Visibility into Application Performance APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month Monitor end-to-end web transactions and take corrective actions now Troubleshoot faster and improve end-user experience. Signup Now! http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140 _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
