Hyrbid Model for Diabetes Predictions-

Objective The objective of creating a diabetes prediction model is to develop a machine learning algorithm that can accurately predict the likelihood of a person developing diabetes based on certain features or risk factors. The model aims to assist healthcare professionals in early detection and intervention, allowing them to provide personalized preventive care and guidance to individuals at higher risk of diabetes. By identifying individuals who are more likely to develop diabetes, it becomes possible to take proactive measures to prevent or delay the onset of the disease, improving overall health outcomes and reducing the burden on healthcare systems.

1. Techniques Used
   1. Data Cleaning
   2. Data Visualization
   3. Machine Learning Modeling
2. Algorithms Used
   1. K-Means Clustering
   2. Decision Tree Classifier
3. Model Evaluation Methods Used
   1. Accuracy Score
4. Packages and Tools Required
   1. Pandas
   2. Matplotlib
   3. Seaborn
   4. Scikit Learn
   5. Jupyter Notebook
5. Package Installation
   1. pip install numpy
   2. pip install pandas
   3. pip install seaborn
   4. pip install scikit-learn
   5. pip install matplotlib