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Predictive-Analysis-and-Review

CERTIFICATE MACHINE LEARNING TERAPAN DICODING

SUBMISSION : "Predictive analysis and Review " , COURSE MACHINE LEARNING TERAPAN dicoding. The dataset used in this report is flight fare data in India in 2019 "Flight Fare Prediction" The purpose or target of this dataset is to analyze data and build a prediction model that can predict airplane ticket prices based on these features. By using 3 models namely K-Nearest Neighbor (KNN) Regression, Random Forest Regression, and Decision Tree Regression. And at the evaluation stage using 3 metrics namely R2_Score, MAE, and MSE. From the evaluation results it was found that the best model for this dataset was Random Forest Regression with R2_score training > 94% and test > 82% so it has good fit results.

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