Showing results for Digestive Vector
GitHub Repo
https://github.com/sanjidaislam251/Diabetes_Prediction
sanjidaislam251/Diabetes_Prediction
The objective of this project is to predict whether or not a participant is diabetic. We will be applying a Support Vector Classifier model to classify diabetes. The datasets used for this project is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. All participants of the dataset are females of Pima Indian heritage that are at least 21 years old. The attributes of this dataset are based on diagnostic measurements such as blood pressure and BMI.
GitHub Repo
https://github.com/Anmol-Jain777/Prima-Indian-Diabetes-prediction
Anmol-Jain777/Prima-Indian-Diabetes-prediction
Description about dataset The Prima Indian Diabetes Dataset has been used in this study, provided by the UCI Machine Learning Repository. The dataset has been originally collected from the National Institute of Diabetes and Digestive and Kidney Diseases. The dataset consists of some medical distinct variables, such as pregnancy record, BMI, insulin level, age, glucose concentration, diastolic blood pressure, triceps skin fold thickness, diabetes pedigree function etc. This dataset has 768 patient’s data where all the patients are female and at least 21 years old. The number of true cases are 268 (34.90%) and the number of false cases are 500 (65.10%), respectively, in the dataset. I used six classification techniques, artificial neural network (ANN), Support Vector Machine (SVM), Decision tree (DT), random forest (RF), Logistics Regression (LR) and Naïve Bayes (NB).
GitHub Repo
https://github.com/bHup12/diabetisprediction