PariyaPm / ML_Models

This repository has the codes for predicting land cover for binary data

ML_Models

This repository has the codes for predicting land cover for binary data using four classification Machine Learning algorithms of SVM, Logistic Regression, and ensemble algorithms of Random Forest and Voting Classifier. The repo. has all the necessary elements to run ML classifiers for a binary land cover predictions.

The repo includes: data, Models, and spatialEnv directories.

Data

This Folder includes the sample data for the developed models. We have one .txt file per variable and the dataPrep.py model will read the files to cunstruct the training-test-validation data.

Model

Model directory includes .py codes for the data preprocessing and ML Models. The .py files in this directory include: RandomData, dataPrep, fourModels, and dataType

spatialEnv

This directory is the virtual environment. All the requirements of the model are stored in spatialEnv directory.