概述
Learning
6 models are used in the learning steps: K-Nearest Neighbor, perception, decision tree, support vector machine, multi-layer perception and Na?ve Bayesian. I designed a RBF classifier and MLP classifier at first but they are too slow for the reason that matrix manipulation hasn’t been designed carefully, so I use the function in the library instead. Parameter determination for these classifiers are:
①K-NN
When k≥5，the accuracy trends to be stable, so k=5
②Decision tree
Maxcrit is used as binary splitting criterion.
③MLP
5 units for hidden is enough
最后
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