Installation:

pip install deepsurv

py.test

Training a Network:

Training DeepSurv can be done in a few lines. First, all you need to do is prepare the datasets to have the following keys:

{
        'x': (n,d) observations (dtype = float32),
        't': (n) event times (dtype = float32),
        'e': (n) event indicators (dtype = int32)
}

Then prepare a dictionary of hyper-parameters. And it takes only two lines to train a network:

network = deepsurv.DeepSurv(**hyperparams)
log = network.train(train_data, valid_data, n_epochs=500)

You can then evaluate its success on testing data:

network.get_concordance_index(**test_data)
>> 0.62269622730138632

If you have matplotlib installed, you can visualize the training and validation curves after training the network:

deepsurv.plot_log(log)

License:

MIT License

Copyright (c) 2016, Jared Katzman

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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