Flight Fare Predictor

Introduction

Flight ticket costs, as we all know, may be difficult to predict. As a result, we attempted to forecast the pricing for future trip dates. To do so, we used web scraped data from my journey to make the forecast.

Steps done-

• 1. EDA for extracting the possible features, trends in data and detecting outliers.
• 2. Feature Extraction
• 3. Feature Selection using FFS and Ensemble Learning
• 4. Test
• 5. Prediction

Algorithms for Model Building Used

Algorithm	Obtained R2 Score
Linear Regression	0.21
Support Vector Regressor	0.10]
XGBoost (Tree based)	0.48
Random Forest	0.61

For getting more insights- view the PPT