QDA Module

A Quadratic Discriminant Analysis (QDA)

The doc is here : http://scikit-learn.org/dev/modules/generated/sklearn.qda.QDA.html#sklearn.qda.QDA

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Sortie du script

$ python QDA.py
Opening the file 'train.csv' and 'test.csv'...
Learning...
 Proportion of perfect fitting for the training dataset = 80.58%
Class priors (sum to 1) = [ 0.61616162  0.38383838].
	For the attribute pclass	, mean=[ 2.53187614  1.9502924 ].
	For the attribute sex	, mean=[ 0.85245902  0.31871345].
	For the attribute age	, mean=[ 0.38018875  0.35687223].
	For the attribute sibsp	, mean=[ 0.55373406  0.47368421].
	For the attribute parch	, mean=[ 0.32969035  0.46491228].
	For the attribute fare	, mean=[ 0.04317124  0.09446154].
	For the attribute embarked	, mean=[ 0.94899818  0.81578947].
 Score for test part = 81.63%
 Score for test part = 81.97%
 Score for test part = 74.15%
 Score for test part = 79.59%
 Score for test part = 83.67%
Predicting for the testing dataset
Prediction: wrote in the file csv/QDA_best.csv.

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QDA.score = 77.210884353741491

The score for this classifier.