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# Diabetes Prediction |
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# Diabetes Prediction |
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Using various machine learning algorithms to get the best prediction accuracy if possible for the Pima Indians dataset. |
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Using various machine learning algorithms to get the best prediction accuracy if possible for the Pima Indians dataset. |
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The best result was found with GradientBoosting with an accuracy of 83%. |
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The best result was found with GradientBoosting with an accuracy of 83%. |
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## Install |
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## Install |
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### Python version used in this project: 3.6.6 |
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### Python version used in this project: 3.6.6 |
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### Libraries used: |
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### Libraries used: |
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> * [Pandas](http://pandas.pydata.org) 0.23.4 |
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* [Pandas](http://pandas.pydata.org) 0.23.4
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> * [Numpy](http://www.numpy.org) 1.15.3 |
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* [Numpy](http://www.numpy.org) 1.15.3
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> * [Matplotlib](https://matplotlib.org) 2.2.2 |
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* [Matplotlib](https://matplotlib.org) 2.2.2
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> * [Scikit-learn](http://scikit-learn.org/stable/) 0.20.0 |
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* [Scikit-learn](http://scikit-learn.org/stable/) 0.20.0
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> * [Scipy](https://www.scipy.org/) 1.1.0 |
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* [Scipy](https://www.scipy.org/) 1.1.0 |
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## How to Run |
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## How to Run |
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To run this project you will need some software, like Anaconda. |
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To run this project you will need some software, like Anaconda. |
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From Anaconda just set as working directory the folder of the project, open the .py file you want from Models folder and run this file or press F5. |
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From Anaconda just set as working directory the folder of the project, open the .py file you want from Models folder and run this file or press F5.
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