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This project aims to develop a machine learning model for predicting chronic kidney disease (CKD) using the Fuzzy K-Nearest Neighbors (F-KNN)

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DikkiKartajaya/ChronicKidneyDisease-FuzzyKNN

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Chronic Kidney Disease Prediction using Fuzzy K-Nearest Neighbors algorithm

Overview :

This project aims to develop a machine learning model for predicting chronic kidney disease (CKD) using the Fuzzy K-Nearest Neighbors (Fuzzy KNN) algorithm. Chronic kidney disease is a significant health concern globally, and early detection plays a crucial role in effective management and treatment. Machine learning techniques, particularly Fuzzy KNN, offer a promising approach for accurate prediction.

Requirements :

  • numpy
  • pandas
  • matplotlib
  • seaborn
  • scikit-learn
  • scipy

Dataset :

Dataset Source : Kaggle

Attribute Name Actual Name Attribute Name Actual Name
age Age sod sodium
bp blood pressure pot potassium
sg specific gravity hemo hemoglobin
al albumin pcv packed cell volume
su sugar wc white blood cell count
rbc red blood cells rc red blood cell count
pc pus cell htn hypertension
pcc pus cell clumps dm diabetes mellitus
ba bacteria cad coronary artery disease
bgr blood glucose random appet appetite
bu blood urea pe pedal edema
sc serum creatinine ane anemia
pcc pus cell clumps class class

Methodology:

  1. Data Preprocessing: Cleaning the dataset, Changing Attribute Name, handling missing values, and encoding categorical & nominal.
  2. Feature Selection: Identifying relevant features that contribute significantly to the prediction of CKD.
  3. Model Training: Implementing the Fuzzy k-NN algorithm.
  4. Model Evaluation: Assessing the performance of the model using appropriate metrics such as accuracy, precision, recall, and F1-score.

Preview

Dataset Preview

Dataset Preview

Fuzzy K-Nearest Neighbors Formula & Accuracy Result

Dataset Preview Dataset Preview

Usage

  1. Clone the repository :
git clone https://github.com/DikkiKartajaya/ChronicKidneyDisease-FuzzyKNN.git
  1. Install the required dependencies :
pip install -r requirement.txt
  1. Run the Jupyter notebook Kidneydisease_FuzzyKNN.ipynb to train and evaluate the Fuzzy KNN model.

Contribution :

Contributions to the project are welcome! If you have any suggestions for improvement, feature requests, or bug reports, please feel free to open an issue or submit a pull request.

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This project aims to develop a machine learning model for predicting chronic kidney disease (CKD) using the Fuzzy K-Nearest Neighbors (F-KNN)

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