Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.

Filename	Size	Update
lab3	0	2019-03-31
lab3\GaussianNB-house-matplotlib.png	15026	2019-03-22
lab3\GaussianNB-segment-matplotlib.png	30364	2019-03-21
lab3\house-votes-84.data	18171	2016-03-16
lab3\house-votes-84.names	7059	2016-03-16
lab3\knn-house-matplotlib.png	15725	2019-03-22
lab3\knn-house.py	5523	2019-03-22
lab3\knn-segment-matplotlib.png	29129	2019-03-22
lab3\knn-segment.py	5546	2019-03-22
lab3\MultinomialNB-house-matplotlib.png	14986	2019-03-22
lab3\MultinomialNB-segment-matplotlib.png	31075	2019-03-21
lab3\naive-bayes-house.py	4183	2019-03-21
lab3\naive-bayes-segment.py	5368	2019-03-21
lab3\segment-tain.txt	200410	2007-10-11
lab3\segment-test.txt	109984	2007-10-11
lab3\tree-house-graphviz.dot	1453	2019-03-22
lab3\tree-house-graphviz.png	75493	2019-03-22
lab3\tree-house-matplotlib.png	16219	2019-03-22
lab3\tree-house.py	5870	2019-03-22
lab3\tree-segment-graphviz.dot	17529	2019-03-22
lab3\tree-segment-graphviz.png	1011689	2019-03-22
lab3\tree-segment-matplotlib.png	41287	2019-03-22
lab3\tree-segment.py	6706	2019-03-22

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