Todo:
- choose layerwise training or not
- add weight decay
- changing the weight initialization
- specify random seed
Autoencoder implemented in tensorflow
positional arguments: fpath Path to file containing matrix with input examples for the autoencoder
optional arguments: -h, --help show this help message and exit -T, --transpose Transpose input -n N_HIDDEN_NODES [N_HIDDEN_NODES ...], --n_hidden_nodes N_HIDDEN_NODES [N_HIDDEN_NODES ...] Number of hidden nodes in each hidden layer -l LEARNING_RATE, --learning_rate LEARNING_RATE Learning rate -d DROPOUT_PROB, --dropout_prob DROPOUT_PROB Dropout probability -c N_CYCLES, --n_cycles N_CYCLES Number of training cycles -b BATCH_SIZE, --batch_size BATCH_SIZE Number of training examples per cycle --no_scaling Do not scale input (use this if you have already scaled it) --no_output Skip writing encoded and decoded values to file? --decoded_file DECODED_FILE Name of file to write decoded (reconstructed) values to --encoded_file ENCODED_FILE Name of file to write encoded values to --scaled_input_file SCALED_INPUT_FILE Name of file to write scaled input values to