In this Diabetes Prediction using Machine Learning Project Code, the objective is to predict whether the person has Diabetes or not based on various features like Number of Pregnancies, Insulin Level, Age, BMI. The objective of this project is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
- Predict whether the person has diabetes or not?
- Prepare the dataset using several methods to train the model.
- Prepare a model which will give high accuracy of predicting the disease.
- Proposed model makes prediction based on some attributes.
- Model is able to predict that the person has the diabetics or not with the accuracy of 78 %.
- Model require inputs like: -Pregnancies, Glucose level, Blood Pressure, Skin Thickness, Insulin, BMI, Diabetics Pedegree function, Age to calculate the sales accurately.
Python libraries:
- Pandas
- Numpy
- Sklearn
Algorithm:
- Support Vector Machine
- Logistic Regression
Firstly, we import the dataset of diabetics. Then we do some data cleaning process. Data visualization is done afterwards. Now, we have cleaned data so with the help of train_test_split(), we divide the dataset. Support Vector Machine and Logistic Regression Models are used for predicting that the person has diabetics or not? The above part comes under backend.