ryMnistClassifiers

In this blog, I have succeeded in doing a classification task on MNist database.

Based on sklearn, I have tried Perceptron, svm, and gmm.
In addition to those, I also found a mlp.py in Github and debug it to run in Python 3.

So I have 4 types of classifiers now.

At first, I hope to make things as simple as possible, so I tend to use the simplest setting for each classifiers, usually using their default values.

Since the MNist database is not small, so I haven't used all of it at first,
Because there are so many parameters to be set, doing some smaller test is necessary,

So I only take 1/10 of MNist dataset to train all the classifiers.

you can see that in the program ryMnistClassifiers03.py ,

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ryMnistClassifiers02.py 

(the training/testing overlap has been debugged)

(But I found svm is very poor in this experiment, so I still need to modify it)

Perceptron

mlp

svm

gmm

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ryMnistClassifiers.py 

(It seems that much of testing data is overlapped with training data!)

so the 100% for svm and gmm is not real!!

trainingdata

perceptron

mlp

svm/gmm

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