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Binary classification model using PyTorch to predict heart failure using clinical data.

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Classification

A classification algorithm in machine learning is used to categorize data into predefined classes or labels. It learns from training data with known class labels and makes predictions on new, unseen data based on learned patterns. Examples include logistic regression, decision trees, support vector machines, and neural networks. These algorithms output a class label, such as 'spam' or 'not spam,' based on the input features

Dataset

  1. [Kaggle] Heart Failure:
    https://www.kaggle.com/datasets/fedesoriano/heart-failure-prediction
  2. [UC Irvine] Heart Failure:
    https://archive.ics.uci.edu/dataset/519/heart+failure+clinical+records

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Binary classification model using PyTorch to predict heart failure using clinical data.

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