agarwalgarimap/Algerian-forest-fire-project-Regression-and-Classification-both
Domain:
environment and energyRecord type:
datasetproject
Creator:
aga
Host:
# Algerian-forest-fire-project-Regression-and-Classification-both
### A brief description of what this project is all about.
Forest Fire Prediction is a Supervised Machine learning problem statements. Using Regression and Classification Algorithm, Regression and Classification Model is build that detected future fires based on certain Weather report.
## Library Used in this Project
Data Pre-Processing
Numpy, Pandas, Matplotlib, Seaborn
Model Building
Sklearn, statsmodels
Hyperparameter Tuning
RandomizedSearchCV, GridSearchCV
## Introduction
Algerian Forest Fires
Data Set Information:
The dataset includes 244 instances that regroup a data of two regions of Algeria,namely the
Bejaia region located in the northeast of Algeria and the Sidi Bel-abbes region located in the northwest of Algeria.
122 instances for each region.
The period from June 2012 to September 2012.
The dataset includes 11 attribues and 1 output attribue (class)
The 244 instances have been classified into fire (138 classes) and not fire (106 classes) classes.
Attribute Information:
1. Date : (DD/MM/YYYY) Day, month ('june' to 'september'), year (2012)
Weather data observations
2. Temp : temperature noon (temperature max) in Celsius degrees: 22 to 42
3. RH : Relative Humidity in %: 21 to 90
4. Ws : Wind speed in km/h: 6 to 29
5. Rain: total day in mm: 0 to 16.8
FWI Components
6. Fine Fuel Moisture Code (FFMC) index from the FWI system: 28.6 to 92.5
7. Duff Moisture Code (DMC) index from the FWI system: 1.1 to 65.9
8. Drought Code (DC) index from the FWI system: 7 to 220.4
9. Initial Spread Index (ISI) index from the FWI system: 0 to 18.5
10. Buildup Index (BUI) index from the FWI system: 1.1 to 68
11. Fire Weather Index (FWI) Index: 0 to 31.1
12. Classes: two classes, namely Fire and not Fire
## Steps
Data Collection
Data Pre-Processing
Exploratory Data Analysis
Feature Engineering
Feature Selection
Model Building
Model Selection
Hyperparameter Tuning
Flask framework
Model d …