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- from modules.config.attributes_config import *
- # store all variables from global config
- context_vars = vars()
- # folders
- ## min_max_custom_folder = 'custom_norm'
- ## correlation_indices_folder = 'corr_indices'
- # variables
- features_choices_labels = ['lab', 'mscn', 'low_bits_2', 'low_bits_3', 'low_bits_4', 'low_bits_5', 'low_bits_6','low_bits_4_shifted_2', 'sub_blocks_stats', 'sub_blocks_area', 'sub_blocks_stats_reduced', 'sub_blocks_area_normed', 'mscn_var_4', 'mscn_var_16', 'mscn_var_64', 'mscn_var_16_max', 'mscn_var_64_max', 'ica_diff', 'svd_trunc_diff', 'ipca_diff', 'svd_reconstruct', 'highest_sv_std_filters', 'lowest_sv_std_filters', 'highest_wave_sv_std_filters', 'lowest_wave_sv_std_filters', 'highest_sv_std_filters_full', 'lowest_sv_std_filters_full', 'highest_sv_entropy_std_filters', 'lowest_sv_entropy_std_filters', 'convolutional_kernels_std_normed', 'convolutional_kernels_mean_normed', 'convolutional_kernels_std_max_blocks', 'convolutional_kernels_mean_max_blocks']
- ## models_names_list = ["svm_model","ensemble_model","ensemble_model_v2","deep_keras"]
- ## normalization_choices = ['svd', 'svdn', 'svdne']
- # parameters
- ## keras_epochs = 500
- ## keras_batch = 32
- ## val_dataset_size = 0.2
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