29 lines
632 B
Python
29 lines
632 B
Python
import os
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os.environ["TF_ENABLE_ONEDNN_OPTS"] = "0"
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from keras.models import load_model
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import pandas as pd
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from sklearn.metrics import confusion_matrix
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import numpy as np
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def main():
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model = load_model("model/model.keras")
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X_test = pd.read_csv("data/X_test.csv")
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y_test = pd.read_csv("data/y_test.csv")
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y_pred = model.predict(X_test)
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y_pred = y_pred >= 0.5
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np.savetxt("data/y_pred.csv", y_pred, delimiter=",")
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cm = confusion_matrix(y_test, y_pred)
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print(
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"Recall metric in the testing dataset: ",
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cm[1, 1] / (cm[1, 0] + cm[1, 1]),
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)
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if __name__ == "__main__":
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main()
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