#! bin/bash # erase "results/models_comparisons.csv" file and write new header file_path='results/models_comparisons.csv' erased=$1 if [ "${erased}" == "Y" ]; then echo "Previous data file erased..." rm ${file_path} mkdir -p results touch ${file_path} # add of header echo 'model_name; vector_size; start; end; nb_zones; feature; mode; tran_size; val_size; test_size; train_pct_size; val_pct_size; test_pct_size; train_acc; val_acc; test_acc; all_acc; F1_train; recall_train; roc_auc_train; F1_val; recall_val; roc_auc_val; F1_test; recall_test; roc_auc_test; F1_all; recall_all; roc_auc_all;' >> ${file_path} fi start_index=0 end_index=24 # selection of four scenes (only maxwell) scenes="A, D, G, H" feature="lab" for label in {"0","1"}; do for highest in {"0","1"}; do for nb_zones in {4,6,8,10,12}; do for size in {5,10,15,20,25,30,35,40}; do for mode in {"svd","svdn","svdne"}; do for model in {"svm_model","ensemble_model","ensemble_model_v2"}; do FILENAME="data/${model}_N${size}_B${start_index}_E${size}_nb_zones_${nb_zones}_${feature}_${mode}_corr_L${label}_H${highest}" MODEL_NAME="${model}_N${size}_B${start_index}_E${size}_nb_zones_${nb_zones}_${feature}_${mode}_corr_L${label}_H${highest}" echo $FILENAME # only compute if necessary (perhaps server will fall.. Just in case) if grep -q "${MODEL_NAME}" "${file_path}"; then echo "${MODEL_NAME} results already generated..." else python generate/generate_data_model_corr_random.py --output ${FILENAME} --n ${size} --highest ${highest} --label ${label} --kind ${mode} --feature ${feature} --scenes "${scenes}" --nb_zones "${nb_zones}" --percent 1 --renderer "maxwell" --step 10 --random 1 --custom 1 python train_model.py --data ${FILENAME} --output ${MODEL_NAME} --choice ${model} # use of interval but it is not really an interval.. python others/save_model_result_in_md_maxwell.py --interval "${start_index},${size}" --model "saved_models/${MODEL_NAME}.joblib" --mode "${mode}" --feature ${feature} fi done done done done done done