Forest Cover Type Classification

GOAL

The main goal of this project to classify the cover type of forest with the dataset.

DATASET

The data set is taken from the Kagle. Click here

WHAT I HAD DONE Listed down the step by step procedure of how project works using points.

• Importing the required modules
• Loading the dataset using pandas module
• Analysing and cleaning the dataset
• Using matplotlib visualising the data.
• Using seaborn to visualize pictographically.
• Using seaborn to see the aspect, elevation and slope of the forest range.
• Generated the Heatmap.
• Design a modelusing classification
• Predicted the result using the dataset.

MODELS USED

The RandomForest Classifier model is used and easily implemented to gives better classification result.

LIBRARIES NEEDED Add all the libraries needed in this project

• pandas
• numpy
• matplotlib
• sklearn
• seaborn

CONCLUSION

Random score is 0.9431.