def train(algorithm, args):
if algorithm == "mc_svm":
# create multiclass SVM model
return MultiSVM()
elif algorithm == "struct_svm":
return StructuredSVM(args.iterations)
elif algorithm == "quad_kernel":
return StructuredSVM(lambda_fn=lambda x, y: x.dot(y)**2)
elif algorithm == "rbf_kernel":
return StructuredSVM(lambda_fn=lambda x, y: math.e**
(-np.linalg.norm(x - y)**2 / (2000)))
elif algorithm == "cnn":
# train a neural network
nn = CNN((128, 128, 3))
nn.add_convolution_layer(nodes=32, size=(3, 3))
nn.add_relu_layer()
nn.add_pool_layer(shape=(1, 1, 2))
nn.add_convolution_layer(nodes=1, size=(3, 3))
nn.add_fc_output_layer(nodes=6)
return nn
return None
