This is a Machine Learning model which predicts the presence of Diabetes in Patients

Last update: Mar 16, 2022

Overview

Diabetes Disease Prediction

This is a machine Learning mode which tries to determine if a person has a diabetes or not.

Data

The dataset is in comma seperated values (.csv) format and is included in teh code.

Packages Used

The following Packages were used

scikit-learn: To preprocess the data, initiate the model, split the data, cross-validate the data and score the model.
pandas: To import the dataset, change the dataset into a dataframe and view the data
seaborn & matplotlib: To visualize the data and to create heat maps to perform feature selection.

Model

Two models were used in this project:

The KNearestNeaighbor Classifier.
The Multi-Layer Perceptron Classifier.

Model Accuracy

The KNearestNeighborClassifier model recorded an accuracy of 72% on the test data.
The MultiLayerPerceptronClassifier model recorded an accuracy of 74% on the test data.

Owner

Edem Gold

Technophile, Machine Learning Engineer.

GitHub Repository https://goldedem.hashnode.dev

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