From c1271fb458a6453d73a23747036fa3ec08119120 Mon Sep 17 00:00:00 2001 From: eugene Date: Tue, 6 Jun 2023 22:38:32 +0200 Subject: [PATCH] upd scr --- script5_4.py | 10 +--------- 1 file changed, 1 insertion(+), 9 deletions(-) diff --git a/script5_4.py b/script5_4.py index ea63d99..73c590b 100644 --- a/script5_4.py +++ b/script5_4.py @@ -4,7 +4,7 @@ import torch.nn as nn from torch.utils.data import DataLoader, Dataset from sklearn.model_selection import train_test_split from sklearn.preprocessing import LabelEncoder -from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, mean_squared_error +from sklearn.metrics import mean_squared_error import pickle # Define the neural network model @@ -75,14 +75,6 @@ for inputs, targets_batch in test_dataloader: predictions = torch.FloatTensor(predictions).squeeze() targets = torch.FloatTensor(targets).squeeze() -accuracy = accuracy_score(targets, torch.round(predictions)) -precision = precision_score(targets, torch.round(predictions), average='micro') -recall = recall_score(targets, torch.round(predictions), average='micro') -f1 = f1_score(targets, torch.round(predictions), average='micro') rmse = mean_squared_error(targets, predictions, squared=False) -print("Accuracy:", accuracy) -print("Micro-average Precision:", precision) -print("Micro-average Recall:", recall) -print("F1 Score:", f1) print("RMSE:", rmse)