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neuralnets_simple_modular.py
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neuralnets_simple_modular.py
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#!/usr/bin/env python
traindat = '../data/fm_train_real.dat'
testdat = '../data/fm_test_real.dat'
label_traindat = '../data/label_train_twoclass.dat'
parameter_list = [[traindat,testdat,label_traindat,0.9,1e-3],[traindat,testdat,label_traindat,0.8,1e-2]]
def neuralnets_simple_modular (train_fname, test_fname,
label_fname, C, epsilon):
from modshogun import NeuralLayers, NeuralNetwork, RealFeatures, BinaryLabels
from modshogun import Math_init_random, CSVFile
Math_init_random(17)
feats_train=RealFeatures(CSVFile(train_fname))
feats_test=RealFeatures(CSVFile(test_fname))
labels=BinaryLabels(CSVFile(label_fname))
layers = NeuralLayers()
network = NeuralNetwork(layers.input(feats_train.get_num_features()).linear(50).softmax(2).done())
network.quick_connect()
network.initialize_neural_network()
network.set_labels(labels)
network.train(feats_train)
return network, network.apply_multiclass(feats_test)
if __name__=='__main__':
print('Neural nets')
neuralnets_simple_modular(*parameter_list[0])