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Binary classification for Airline arrival delay without using departure delay predictors

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Airline-On-Time-Arrivals

Binary classification for Airline arrival delay without using departure delay predictors

Python Notebook is available in the repository and dataset can be downloaded from the link: https://transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time Please download with Prezipped check box selected and Filter setting was Filter Geography: All Filter Year: 2017 Filter Month: January

This notebook was created for startupML challenge 2017

Please keep in mind that I only used 2-fold cross validation to save time. Best estimate is given my leave-one-out cross validation. Which uses all samples for training except one sample for validation and repeats for each sample. Unfortunately it is very expensive. Usually 10-fold cv is recommended. So as long as system and time allows go for as many folds as you can afford.

Author: Muaaz Bin Sarfaraz

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