Diabetes Detection using a Neuro-Fuzzy System

Combines fuzzy-c-means feature generation with a neural-network classifier to predict diabetes outcomes on the Pima Indians dataset.

Python 3 pandas NumPy scikit-learn skfuzzy matplotlib
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Project Overview

The notebook loads the Pima Indians Diabetes dataset into a DataFrame (768 × 9) via pandas , applies standard scaling, then generates fuzzy membership features using a C-means clustering implementation . It concatenates these fuzzy features with the original scaled inputs to train both a baseline MLP (via TensorFlow/Keras) and a hybrid Neuro-Fuzzy model, comparing their performance through accuracy and other classification metrics.

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Project Details

  • Completion Date March 2025
  • Category Machine Learning
  • Project Type HTML File

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Diabetes Detection using a Neuro-Fuzzy System