It is type of regression problem whcih can be tried to solve using two approaches
1.XGBoost with hypertunning.
2.Random forest with hypertunning.
This two algorithms had their own importance and uses.The xgboost is used in many competitions.
Here hypertuning is performed with GreadySearch which intially takes some intial parameter values
then it will search for parameter values which increases the accuracy of model.So some details about problems are
•The goal is to find item sale at Outlet of different types & located at different locations.
•It includes task such as data visualization, cleaning and transformation,feature engineering.
•Python is used as programming language and Jupyter Notebook is used as tools.
•packages used are
1.pandas.
2.numpy.
3.sklearn.
4.matplotlib.
Before Better understanding i will provide few links which might be useful for better understanding
- https://www.analyticsvidhya.com/blog/2016/04/complete-tutorial-tree-based-modeling-scratch-in-python
- https://www.analyticsvidhya.com/blog/2015/01/decision-tree-simplified/2/
- https://www.datascience.com/resources/notebooks/random-forest-intro
- https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/