Price_Prediction_Models
Basic to complex prediction model using exhaustive selector & Lasso CV
AIRFARE Dataset - Predicting airline fare
Boston Housing - House Pricing Prediction
Toyota Dataset - Car Pricing Model
Used - from mlxtend.feature_selection import ExhaustiveFeatureSelector to select the best features
Exhaustive Selector selects best features on the K value mentioned by us where K = Number of features required. It chooses features on the based of the Score mentioned by us.
You can mention the Score value depending upon the business statement/requirement Check P>|t| value and Adjusted R-Square values for better accuracy
For better results check MAPE of training & testing dataset
Now applied Losso for cross validation calculating optimum Alpha value
Result - Regression model for price prediction.