Mushroom Classification with SVM using R

This project implements a Support Vector Machine (SVM) model for classifying mushrooms into edible and poisonous categories using R programming language.

Project Structure

• Data Exploration: Investigates the dataset, visualizes class distributions, and explores feature relationships.
• Data Preprocessing: Cleans the dataset, removes irrelevant features, and splits data into training and testing sets.
• Model Training: Utilizes SVM to build a classification model on the training data.
• Performance Evaluation: Evaluates the model's performance using confusion matrix, precision, recall, and F-measure.

Dependencies

• plotly
• kernlab
• ggplot2
• visdat
• lattice
• caret
• e1071

Usage

1. Clone the repository:

git clone https://github.com/jrzvnn/mushroom-svm.git

2. Run the R script:

Rscript mushroom_svm.R

3. View the model performance and analysis results.