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.