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import os |
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BASE_DIR = os.path.abspath(os.path.dirname(__file__)) |
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DATA_PATH = os.path.join(BASE_DIR, "data", "synthetic_transactions_samples_5000.csv") |
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MODEL_SAVE_DIR = os.path.join(BASE_DIR, "models") |
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LABEL_ENCODERS_PATH = os.path.join(MODEL_SAVE_DIR, "label_encoders.pkl") |
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TFIDF_VECTORIZER_PATH = os.path.join(MODEL_SAVE_DIR, "tfidf_vectorizer.pkl") |
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MODEL_PATH = os.path.join(MODEL_SAVE_DIR, "xgb_models.pkl") |
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TEXT_COLUMN = "Sanction_Context" |
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LABEL_COLUMNS = [ |
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"Red_Flag_Reason", |
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"Maker_Action", |
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"Escalation_Level", |
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"Risk_Category", |
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"Risk_Drivers", |
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"Investigation_Outcome" |
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] |
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TFIDF_MAX_FEATURES = 5000 |
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NGRAM_RANGE = (1, 2) |
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USE_STOPWORDS = True |
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RANDOM_STATE = 42 |
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TEST_SIZE = 0.2 |
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