laksh1701 / diabetes-prediction-using-logistic-regression

This project objective is to predict the type 2 diabetes, based on the dataset.

Diabetes-prediction

This project objective is to predict type 2 diabetes, based on the dataset. This application gets details from the user such as Glucose level, Insulin, Age, BMI, etc ad predict whether the user has diabetes or not.

Pima Indians Diabetes Database

https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database

Description of variables in the dataset:

 Pregnancies: Number of times pregnant
 Glucose: Plasma glucose concentration a 2 hours in an oral glucose tolerance test
 BloodPressure: Diastolic blood pressure (mm Hg)
 SkinThickness:Triceps skin fold thickness (mm)
 Insulin: 2-Hour serum insulin (mu U/ml)
 BMI: Body mass index (weight in kg/(height in m)²)
 DiabetesPedigreeFunction: Diabetes pedigree function
 Age: Age (years)
 Outcome: Class variable (0 or 1)

Algorithm

Logistic Regression

Logistic regression is a classification model in machine learning, extensively used in clinical analysis. It uses probabilistic estimations which helps in understanding the relationship between the dependent variable and one or more independent variables.

Software Used

Frontend Tools:

HTML CSS

Backed Tools:

Python Flask

Markup Languages

Python

IDE

Visual Studio Code