Reusable Deep Neural Networks:

Applications to Biomedical Data

Generate script to run BASELINE

Enter target dataset and path used for the experiment

Type the path where all the datasets located in Theano pickled format:
Target_dataset:
Type the folder name of target dataset:
Type the folder name to store the results:
Type the text file name to store the console output:
Enter number times to repeate the experiment:
Enter the GPU number used:

Enter Stacked Denoising Autoencoders traning parameters

Fine-tuning learning rate :
Max number of Fine-tuning epochs :
Pre-training learning rate :
Max number of Pre-training epochs :
Number of neurons at each hidden layer comma seperated for each layer eg: [500,500,500]
Mini batch size :
Random initial seed number :
Train fraction of the total training data :

Now Copy and Paste the following into terminal and hit return to prepare tiles:


taskset -c 0 nohup python online_input.py BL target_data data_path fold results_dir nr_reps gpu_nr finetune_lr training_epochs pretrain_lr pretraining_epochs hidden_layers_sizes batch_size rng_seed training_data_fraction > results_dir result_file_name 2>&1 &

This project is financed by FEDER funds through the Programa Operacional Factores de Competitividade COMPETE and by Portuguese funds through FCT Fundação para a Ciência e a Tecnologia in the framework.