ashishrana1501/Forest-Fire-Prediction

Algerian Forest Fire Prediction # Forest Fire Prediction **Heroku App** (forestfire-predictions.hero…) # Demonstration **Classification** user-images.githubuserconte… **Regression** user-images.githubuserconte… ## 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. A framework is created using **Flask** and deployed on **Heroku** ## 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 Available at:** link text ***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 Moi …