The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018) is challenging you to build an algorithm that predicts whether a subscription user will churn using a donated dataset from KKBOX.

KKBox churn prediction challenge on Kaggle: dealing with imbalanced data using WRF, autoencoder and xgboost.

KKBox Churn Prediction

WSDM - KKBox's Churn Prediction Challenge / Can you predict when subscribers will churn?

WSDM - KKBox's Churn Prediction Challenge

kaggle WSDM - KKBox's Churn Prediction Challenge

KKBox's Churn Prediction Challenge

This project is Kaggle Project(Kaggle.com). This project is scripted in R language. Use R Studio for smoother workflow.

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WSDM - KKBox's Churn Prediction Challenge Can you predict when subscribers will churn? This is a model for thematic preparation. I used the dataset of KKBox.

KKbox churn prediction challenge

KKBox's Churn Prediction Challenge (ref: https://www.kaggle.com/c/kkbox-churn-prediction-challenge)

WSDM - KKBox's Churn Prediction Challenge

Documents and codes

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KKBox's Churn Prediction Challenge in Kaggle

Kaggle - WSDM - KKBox's Churn Prediction Challenge

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Repo for working on the KKBox Churn Prediction Challenge https://www.kaggle.com/c/kkbox-churn-prediction-challenge/data

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https://www.kaggle.com/c/kkbox-churn-prediction-challenge/overview

Kaggle project

https://www.kaggle.com/c/kkbox-churn-prediction-challenge/

Business Analytics and Data Mining Project

https://www.kaggle.com/c/kkbox-churn-prediction-challenge

WSDM - KKBox's Churn Prediction Challenge / Can you predict when subscribers will churn?

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The competition on Kaggle, which names "WSDM - KKBox's Churn Prediction Challenge"