# Rest of your processing code...# ...# Process each row in the datafor idx, row in enumerate(data): try: # Check if the row has the expected number of elements expected_number_of_elements = 21 # Set the correct number of elements if len(row) == expected_number_of_elements: # Process each element in the row for i, element in enumerate(row): try: # Your processing code for each element goes here print(f"Element {i + 1}: {element}") # Example: If the element is numeric, you can perform some numeric operations if isinstance(element, (int, float)): # Example operation: square the numeric element squared_element = element ** 2 print(f"Squared element: {squared_element}") # Example: If the element is a string, you can perform string operations elif isinstance(element, str): # Example operation: convert the string to uppercase upper_case_element = element.upper() print(f"Uppercase element: {upper_case_element}") # Add more conditions based on the data types you expect except IndexError as e: print(f"Error processing element {i + 1} in row {idx + 1}: {e}") print("Row:", row) continue # Skip the current element and move to the next one else: print( f"Skipping row {idx + 1}: Unexpected number of elements (Length: {len(row)}, Expected: {expected_number_of_elements})") continue # Skip the current row and move to the next one except IndexError as e: print(f"Error processing row {idx + 1}: {e}") print("Row:", row) print("Length of row:", len(row)) # Add an indented block here to handle the exception # This block can be left empty or you can add specific error handling code pass # Add this line # Debugging: print information for each iteration print(f"Processed row {idx + 1}") # Print some debug information about elems elems = meta._attrnames # Uncomment this line print("Elems:", len(elems)) # Add this line for debugging print("Meta:", meta) # Add this line for debugging try: # Rest of your processing code... # ... except IndexError as e: print(f"Error after processing row {idx + 1}: {e}") except Exception as ex: print(f"An error occurred after processing row {idx + 1}: {ex}")# Calculating average metrics for the ARFF datasettry: # Assuming you have a separate test set for final evaluation y_test_final = [1, 0, 1, 1, 0] y_pred_final = [1, 1, 1, 0, 0] classifier_eval(y_test_final, y_pred_final) # Calculating average metrics avg_PD = sum(pd_list) / len(pd_list) if len(pd_list) > 0 else 'No values in pd_list' avg_PF = sum(pf_list) / len(pf_list) if len(pf_list) > 0 else 'No values in pf_list' avg_balance = sum(bal_list) / len(bal_list) if len(bal_list) > 0 else 'No values in bal_list' avg_FIR = sum(fir_list) / len(fir_list) if len(fir_list) > 0 else 'No values in fir_list' # Print or use the average metrics as needed print('Average PD:', avg_PD) print('Average PF:', avg_PF) print('Average balance:', avg_balance) print('Average FIR:', avg_FIR)except Exception as ex: print(f"An error occurred during final evaluation: {ex}")Getting identification error at try:
# Rest of your processing code... # ... except IndexError as e: print(f"Error after processing row {idx + 1}: {e}") except Exception as ex: print(f"An error occurred after processing row {idx + 1}: {ex}")