Microsoft Malware Prediction

This repository contains the code for a machine learning project aimed at predicting malware infections on Windows machines using the Microsoft Malware Prediction dataset from Kaggle.

Files Description

1. DataPreprocessing.py

   • This script is responsible for cleaning the dataset and performing feature engineering. It includes handling missing values, encoding categorical variables, and preparing the dataset for model training.

2. LogisticRegression.py

   • This script focuses on training a Logistic Regression model. It includes the implementation of the logistic regression algorithm, model training, performance evaluation, and metrics calculation.

3. RandomForest.py

   • This script is dedicated to training a RandomForest classifier. It covers the setup, training, and evaluation of the RandomForest model, including the calculation of various performance metrics.

Dataset

The dataset used for this project is the Microsoft Malware Prediction dataset, which can be downloaded from Kaggle. It includes a wide range of features extracted from Windows machines, such as system configurations, software information, and security settings.

Link to the dataset: Microsoft Malware Prediction - Kaggle

Usage

To use these scripts, first ensure you have downloaded the dataset from Kaggle and have Python installed on your system. Each script can be run independently:

python DataPreprocessing.py
python LogisticRegression.py
python RandomForest.py