len(np.nonzero(coeffs_x)[0])
#write csv for dic_lang_ramus (from chatGPT) # Extract column labels (metrics) columns = set(metric for metrics in dic_lang_ramus.values() for metric in metrics.keys()) columns = ['Language'] + sorted(columns) # Write to CSV file csv_file_path = 'metrics_data.csv' with open(csv_file_path, 'w', newline='') as csvfile: writer = csv.DictWriter(csvfile, fieldnames=columns) # Write header row writer.writeheader() # Write data rows for language, metrics in dic_lang_ramus.items(): row_data = {'Language': language, **metrics} writer.writerow(row_data) print(f'CSV file written successfully at: {csv_file_path}')
#save model from joblib import dump, load dump(model_qda, 'qda.joblib')