GitHub / Mayurgupta3 / Using-Project-Jupyter-and-Machine-learning-to-optimize-the-Prediction-of-Diabetes
The Project uses Pima Indians diabetes data set to predict whether a patient will have diabetes or not based upon patient’s lab test result variables like Glucose, Blood Pressure, etc. using CART decision tree algorithm and K-Nearest Model achieving 75% accuracy. The project involved the use of Python-Scikit Learn, SciPy, Pandas, MatPlotLib and the Jupyter Environment.
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PURL: pkg:github/Mayurgupta3/Using-Project-Jupyter-and-Machine-learning-to-optimize-the-Prediction-of-Diabetes
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 241 KB
Dependencies parsed at: Pending
Created at: almost 7 years ago
Updated at: about 4 years ago
Pushed at: almost 7 years ago
Last synced at: over 2 years ago
Topics: jupyter-notebook, keras-neural-networks, naive-bayes-algorithm, python-script, python3, sklearn-library