Spatial_Data_Analysis_and_Classification_Techniques_using_Python_and_R

This repository contains the implementation and analysis of various spatial data analysis and classification techniques using the Parana dataset from the geoR library. The project explores different models, including simple linear regression, mixed-effects models, Bayesian classifiers, and decision tree classifiers, to understand spatial variation and perform classification tasks.

Table of Contents

• Installation
• Data
• Exploratory Data Analysis
• Models and Analysis
  • Simple Linear Regression
  • Mixed-Effects Model
  • Bayesian Classifier
  • Decision Tree Classifier
• Results
• Conclusion
• Contributing
• License

Installation

To install the necessary libraries, run:

pip install pandas scipy matplotlib seaborn scikit-learn