52 lines
1.9 KiB
Plaintext
52 lines
1.9 KiB
Plaintext
📚 Loading data from Parquet file at '../data/sampled_fakenews_train.parquet'
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📚 Loading data from Parquet file at '../data/sampled_fakenews_valid.parquet'
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📚 Loading data from Parquet file at '../data/sampled_fakenews_test.parquet'
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🧮 Grouping into binary classes...
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🪙 Preprocessing text...
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🔍 Training models...
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📊 Logistic Regression FakeNewsCorpus Performance:
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precision recall f1-score support
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Reliable 0.84 0.90 0.87 54706
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Fake 0.80 0.70 0.75 30584
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accuracy 0.83 85290
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macro avg 0.82 0.80 0.81 85290
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weighted avg 0.83 0.83 0.83 85290
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📊 Naïve Bayes FakeNewsCorpus Performance:
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precision recall f1-score support
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Reliable 0.79 0.92 0.85 54706
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Fake 0.79 0.57 0.67 30584
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accuracy 0.79 85290
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macro avg 0.79 0.74 0.76 85290
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weighted avg 0.79 0.79 0.78 85290
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📚 Loading LIAR dataset...
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🧮 Grouping into binary classes...
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🪙 Preprocessing text...
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📊 Logistic Regression LIAR Performance:
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precision recall f1-score support
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Reliable 0.75 0.79 0.77 926
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Fake 0.32 0.26 0.29 338
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accuracy 0.65 1264
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macro avg 0.53 0.53 0.53 1264
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weighted avg 0.63 0.65 0.64 1264
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📊 Naïve Bayes LIAR Performance:
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precision recall f1-score support
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Reliable 0.74 0.98 0.84 926
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Fake 0.55 0.06 0.11 338
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accuracy 0.74 1264
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macro avg 0.65 0.52 0.48 1264
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weighted avg 0.69 0.74 0.65 1264 |