/Online_Bidding_Classification

Primary LanguageR

This is my solution for the Kaggle competition - Facebook Recruiting IV: Human or Robot?

Facebook Recruiting IV: Human or Robot?

There are two datasets in this competition. One is a bidder dataset that includes a list of bidder information, including their id, payment account, and address. The other is a bid dataset that includes 7.6 million bids on different auctions. The datasets can be downloaded from

Datasets

The solution is done in three seperate R scripts

  • Analysis.R

  • Analysis_testing.R

  • Classification.R

Project Summary

The following are the steps done

  1. Merge the train and the bid datasets by bidder_id to create the training dataset
  2. Check what could be the possible features
  3. Create the Tidy training and testing datasets based on the chosen features
  4. Choose the appropraite classification algorithm based on the ROC test metric
  5. Make the appropraite prediction of the outcome of the testing dataset

Additional Information

You can find additional information about the variables, data and transformations in the CodeBook.md file.