This data is taken from kaggle.
Deleting the huge outliners from data.
Log - transformation of target variable
Feature Engineering for slection of better features for our data.
Data Correlation matrix for viwing the relationship of variables.
There are many missing values in data so we will fill those values as given in the competition rules.
Label Encoding some categorical variables
Using Box Cox Transformation of (highly) skewed features
Importing all required libraries
Cross validation strategy definition
Base models used
1.LASSO Regression
2.Elastic Net Regression
3.Kernel Ridge Regression
4.Gradient Boosting Regression
5.XGBoost
6.LightGBM
Averaged base models class method
Ensembling StackedRegressor, XGBoost and LightGBM
Ensemble prediction and submission.