25 lines
994 B
Python
25 lines
994 B
Python
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, mean_squared_error
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import numpy as np
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true_labels = []
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predicted_labels = []
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f = open("predictions.txt", "r")
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for line in f:
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parts = line.strip().split(' ')
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true_labels.append(int(parts[3]))
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predicted_labels.append(int(parts[1]))
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accuracy = accuracy_score(true_labels, predicted_labels)
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precision_micro = precision_score(true_labels, predicted_labels, average='micro')
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recall_micro = recall_score(true_labels, predicted_labels, average='micro')
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f1_micro = f1_score(true_labels, predicted_labels, average='micro')
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rmse = np.sqrt(mean_squared_error(true_labels, predicted_labels))
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with open(r'metrics.txt', 'a') as fp:
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fp.write(f"Accuracy: {accuracy}\n")
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fp.write(f"Micro-average Precision: {precision_micro}\n")
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fp.write(f"Micro-average Recall: {recall_micro}\n")
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fp.write(f"Micro-average F1-score: {f1_micro}\n")
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fp.write(f"RMSE: {rmse}\n")
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fp.write("--------------------\n") |