The task was to train a Machine Learning model to predict the income based on several inputs/features that were fed to the model. The team used Label Encoder to label the categorical features and trained the data using lightgbm algorithm to attain the result.
The source code is in IncomePrediction.py and uses the following libraries:
- Pandas
- Numpy
- Lightgbm
- Scikit-learn
The final output is stored in 'machinecc learning submitty.csv'.