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This repo is the Machine Learning practice on NHANES dataset of Heart Disease prediction. The ML algorithms like LR, DT, RF, SVM, KNN, NB, MLP, AdaBoost, XGBoost, CatBoost, LightGBM, ExtraTree, etc. The results are good. I also explore the class-balancing (SMOTE) because the original dataset contains only 5% of patient and 95% of healthy record.

  • Updated Apr 13, 2024
  • Jupyter Notebook

This project implements a Disease Prediction System using various machine learning algorithms to predict potential diseases based on user-provided symptoms. The system utilizes a Django web framework to provide a user-friendly interface for inputting symptoms and viewing the predicted disease.

  • Updated Apr 14, 2024
  • Python

Machine Learning algorithms implemented from scratch. Different ML algorithms implemented from scratch. Namely, Multipile Linear Regression and Logistic Regression KNN and Naive Bayes Recrusive Decision Trees Bagging and Boosting (Ada Boost) Yarwosky's Algorithm and Agglomerative Hierarchical Clustering

  • Updated Aug 6, 2019
  • Python

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