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README.md
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## Training and evaluation data
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[Our dataset](https://archive.ics.uci.edu/ml/datasets/heart+Disease) is provided by the Cleveland Clinic Foundation for Heart Disease. It's a CSV file with 303 rows. Each row contains information about a patient (a sample), and each column describes an attribute of the patient (a feature). We use the features to predict whether a patient has a heart disease (binary classification).
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## Training procedure
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Training proceeds for 50 epochs with default Adam optimizer on binary crossentropy.
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## Training and evaluation data
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[Our dataset](https://archive.ics.uci.edu/ml/datasets/heart+Disease) is provided by the Cleveland Clinic Foundation for Heart Disease. It's a CSV file with 303 rows. Each row contains information about a patient (a sample), and each column describes an attribute of the patient (a feature). We use the features to predict whether a patient has a heart disease (binary classification).
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The model is trained on 80% of data and evaluated on remaining 20%.
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## Training procedure
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Training proceeds for 50 epochs with default Adam optimizer on binary crossentropy.
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