gaikwaddarshan0111/Algerian-Forest-Fire-Dataset-EDA-FE-Prediction
Domaine:
environment and energyType de record:
project
Créateur:
gai
Hôte:
This is an normal EDA performed on algerian forest dataset using python libraries.
🔥 Algerian Forest Fire Dataset – EDA, Feature Engineering & Prediction
📌 Project Overview
This project focuses on analyzing the Algerian Forest Fire Dataset and building predictive models to estimate temperature using various regression techniques.
The workflow includes:
Data Cleaning
Exploratory Data Analysis (EDA)
Feature Engineering (FE)
Model Building & Evaluation
🎯 Problem Statement
The goal of this project is to:
Understand patterns in forest fire data
Perform feature engineering for better model performance
Predict temperature using regression models such as:
Linear Regression
Ridge Regression
Lasso Regression
Elastic Net
📂 Dataset Information:
The dataset contains forest fire observations from Algeria with features such as:
Temperature
Relative Humidity (RH)
Wind Speed (Ws)
Rain
Fire Weather Index (FWI)
Other environmental attributes
⚙️ Tech Stack
Language: Python 🐍
Libraries Used:
Pandas
NumPy
Matplotlib
Seaborn
Scikit-learn
🔍 Project Workflow
1️⃣ Data Collection
Dataset loaded and inspected
Initial structure and attributes reviewed
2️⃣ Data Cleaning
Removed incorrect rows (e.g., row 122, 123 issues)
Fixed headers and formatting
Handled missing/invalid values
3️⃣ Exploratory Data Analysis (EDA)
Distribution analysis of features
Correlation heatmaps
Insights on fire vs non-fire conditions
4️⃣ Feature Engineering
Data transformation
Feature selection
Scaling (if applied)
5️⃣ Model Building
Implemented multiple regression models:
Linear Regression
Ridge Regression
Lasso Regression
Elastic Net
6️⃣ Model Evaluation
Compared models using metrics such as:
R² Score
Mean Squared Error (MSE)
Selected best-performing model
📊 Results & Insights
Regression models were successfully trained and evaluated
Regularization techniques (Ridge, Lasso, Elastic Net) helped improve performance and reduce overfitting
Key features influencing temperature prediction were identified
🚀 How to Run This Project
Clone the repository:
git clone github.com …