Python run_neural_net Examples

Example #1

File: neural_network_dim_reduction.py Project: okely-dokely/bag-of-algorithms

def evaluate_nn_accuracy(higgs_data, n_components):
    transformations, times = reduce_higgs(higgs_data, n_components)
    results = []
    for name, transformation in transformations.iteritems():
        data = {'features': transformation, 'weights': higgs_data[1], 'labels': higgs_data[2]}
        nn_res = nn.run_neural_net(data)
        result = [name] + list(nn_res) + [times[name]]
        results.append(result)
    df = pd.DataFrame.from_records(results, columns=['algo', 'epocs', 'trnerr', 'tsterr', 'transformation_time'])
    return df

Example #2

File: clustering_dim_reduction.py Project: okely-dokely/bag-of-algorithms

def neural_net_post_clustering(data):
    return run_neural_net(data)