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from sklearn.linear_model import LogisticRegression
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import joblib
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from commons.Configs import configs
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from commons.File import file
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class Model:
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def __init__(self, debug=False):
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self.debug = debug
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def train(self, x, y):
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return LogisticRegression(solver='lbfgs', random_state=42).fit(x, y)
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def save(self, clf):
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joblib.dump(clf, configs.generatedModelPath)
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print("Model saved to: ", configs.generatedModelPath)
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def load(self):
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if not file.exists(configs.generatedModelPath):
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print("Model not found at: ", configs.generatedModelPath)
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exit(1)
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return joblib.load(configs.generatedModelPath)
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model = Model()
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