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BKMKT

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Bank Marketing Stategy Analysis

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🛠 Contribute : Found a typo? Or any other change in the description that you would like to see ? Please consider sending us a pull request in the public repo of the challenge here.

🕵️ Introduction

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Another one of your beautiful power naps got wrecked by a promotional call? Tired of it yet? Well sometimes the only way to get rid of a problem is to solve it! So put on your smart hats and get rid of your problems once and for all!

Given the history and information of a client, predict if the client will avail the term depsit service.

Understand with code! Here is getting started code for you.😄

💾 Dataset

The dataset basically describes the marketing campaign of a portuguese banking institution. The campaign was based on phone calls and the dataset describes the clients who were contacted, the description also includes the details of previous contacts made to the client as telesales typically need multiple contacts to convince a client.

The final aim of the calls was to convince the client to subscribe to a term deposit. So for each call made to a client you have 20 attributes describing the client and corresponding to a description, there is a final outcome of the call , whether or not the client subscribe to a term deposit. For details about input variable visit here!.

📁 Files

Following files are available in the resources section:

  • train.csv - (32928 samples) This csv file contains the attributes describing information along with the binary value denoting whether or not the client will avail the term deposit service.
  • test.csv - (8238 samples) File that will be used for actual evaluation for the leaderboard score but does not have the binary value denoting whether or not the client will avail the term deposit service.

🚀 Submission

  • Prepare a CSV containing header as y and predicted value as digit yes or no respectively denoting whether or not the client will avail the term deposit service.
  • Name of the above file should be submission.csv.
  • Sample submission format available at sample_submission.csv in the resorces section.

Make your first submission here 🚀 !!

🖊 Evaluation Criteria

During evaluation F1 score will be used to test the efficiency of the model where,

🔗 Links

📱 Contact

📚 References

  • [Moro et al., 2014] S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014
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Getting Started

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