def combine_and_cv(targets, target, ids): combined_dataset, targets = combine_data_from_feature_selection(targets, target) std = StandardizedData(targets) combined_dataset_scaled = std.standardize_dataset(combined_dataset) file_name = "ensemble_theme_" + target + ".txt" for i in range(100): cv10_ensemble(combined_dataset, targets, combined_dataset_scaled, dt, knn, svm_selected_for_features_fusion, fusion_algorithm, ids, prt=True, file_name=file_name)
""" import sys sys.path.insert(0, 'utils/') sys.path.insert(0, 'feature context/') from load_data import * from project_data import * from fusion import cv10_ensemble from fusion import dt from fusion import knn from svms import svm_selected_for_features_fusion from standardized_data import * from thematic_data_combined import combine_data_from_feature_selection from parameters import CV_PERCENTAGE_OCCURENCE_THRESHOLD if __name__ == "__main__": spreadsheet = Spreadsheet(project_data_file) data = Data(spreadsheet) targets = data.targets ids = data.ids fusion_algorithm = raw_input("Enter algorithm. Choose between maj, wmaj, svm, nn") combined_dataset, targets = combine_data_from_feature_selection(targets, CV_PERCENTAGE_OCCURENCE_THRESHOLD) std = StandardizedData(targets) combined_dataset_scaled = std.standardize_dataset(combined_dataset) file_name = fusion_algorithm + "_ensemble_ft.txt" for i in range(100): cv10_ensemble(combined_dataset, targets, combined_dataset_scaled, dt, knn, svm_selected_for_features_fusion, fusion_algorithm, ids, prt=True, file_name=file_name)