SVR Model for Power Consumption Evaluation

This repository contains a Support Vector Regression (SVR) implementation to evaluate model performance using Mean Squared Error (MSE) and R-squared (R2) metrics on a power consumption dataset.

Before Running the Machine Learning Program

Before executing the machine learning program, you need to download the dataset in CSV format from the following Google Drive link.

[https://drive.google.com/drive/folders/1Y8kRoJ6z3oc2aaXjaeUQL9xobzp-ql0C?usp=sharing]

After downloading the dataset, you can import it into your Google Colab environment. Once imported, you can proceed to run the SVR program.

Instructions

1. Download the Dataset:

   • Access the dataset in CSV format from the provided [https://drive.google.com/drive/folders/1Y8kRoJ6z3oc2aaXjaeUQL9xobzp-ql0C?usp=sharing].

2. Import the Dataset in Google Colab:

   • Utilize Google Colab to import the downloaded dataset.

3. Run the SVR Program:

   • After importing the dataset, execute the SVR program to evaluate the model on power consumption data.

Note:

This code may contain some dirty data. You can perform data cleaning to get better insights and conclusions.