Classification of the Spiral dataset

[bermat72]

Hi there, and thank you very much for this brilliant work with MiniDNN.
I am slowly understanding more and more of the code.

Right now I am testing MiniDNN used to classify the the Spiral dataset:
https://cs231n.github.io/neural-networks-case-study/

It doesnt seem to find the optimum.

Any tips on my code, or what optimizer to use?
Have anyone of you tried a testdata for classification?

I would be happy to put together some testdata and make a another tutorial example..... with some help. :)

Sincerely,
Bernt

// Code to read in data and put it into Matrix is scipped.

Network net;
Layer* layer1 = new FullyConnected<Sigmoid>(2, 20);
Layer* layer2 = new FullyConnected<ReLU>(20, 20);
Layer* layer3 = new FullyConnected<Softmax>(20, 3);
net.add_layer(layer1);
net.add_layer(layer2);
net.add_layer(layer3);

net.set_output(new MultiClassEntropy() );

//Adam opt;
//opt.m_lrate = 0.01;
SGD opt;
    
VerboseCallback callback;
net.set_callback(callback);
net.init(0, 0.01, 000);

int nr_epochs = 3000;
net.fit(opt, Xdata.transpose(), Ydata.transpose(), 60, nr_epochs , 000);

Matrix pred = net.predict(Xtest.transpose() );
Matrix P = pred.transpose();

std::cout << P.rows()  << "  " << P.cols() << std::endl;
for(int r = 0; r < P.rows() ; r++){
    std::cout << P(r,0) << " " << P(r,1) << " " << P(r,2) << "\n";
}