🩺 Diabetes Prediction ML Model

📊 Dataset Overview

442

Total Samples

10

Features

221

Diabetes Cases

221

No Diabetes Cases

Dataset Sample

Age	Sex	BMI	BP	S1	S2	S3	S4	S5	S6	Diabetes

Feature Descriptions

Age: Age of the patient

Sex: Sex of the patient (1 = male, -1 = female)

BMI: Body Mass Index

BP: Average Blood Pressure

S1: Total Serum Cholesterol

S2: Low-Density Lipoproteins

S3: High-Density Lipoproteins

S4: Total Cholesterol / HDL

S5: Log of Serum Triglycerides

S6: Blood Sugar Level

Missing Values Check

✅ No missing values found in the dataset!

🔍 Exploratory Data Analysis

Target Variable Distribution

Feature Distributions

Feature Correlation Matrix

Feature Distributions by Diabetes Status

Select feature to analyze:

🤖 Model Training & Evaluation

🔮 Diabetes Prediction Interface

⚠️ Please train the models first in the 'Model Training & Evaluation' page.

Enter Patient Information

Age: 0.0 Standardized age value

Sex:

BMI: 0.0 Standardized BMI value

Blood Pressure: 0.0 Standardized blood pressure value

Total Serum Cholesterol: 0.0 Standardized cholesterol value

Low-Density Lipoproteins: 0.0 Standardized LDL value

High-Density Lipoproteins: 0.0 Standardized HDL value

Total Cholesterol / HDL: 0.0 Standardized cholesterol ratio

Log of Serum Triglycerides: 0.0 Standardized triglycerides value

Blood Sugar Level: 0.0 Standardized blood sugar value