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Project on the use of Knowledge Graph Embeddings for use for a classification problem for Capstone Project submitted for the MSc of Data Analytics

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jamesor19/Knowldge-Graph-Embedding-Model-for-Customer-Churn-Prediction

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Knowldge Graph Embedding Model for Customer Churn Prediction

Capstone Project Master of Data Analytics NUIG

James O'Rourke 15334121

Requirements

  • ampligraph version 1.4.0
  • tensorflow version 1.15.0
  • sckit-learn version 0.24.2
  • numpy version 1.20.3
  • imbalanced-learn version 0.8.0

The contents of the files are as such

  • dataPrep : Juypter notebook with data preperation and creation of knowledge graph
  • experiment : Juypter notebook contains the creation, traning and predcition of the KGE models
  • Baseline Model : Juypter notebook contains the traning, predcition and evaulation of the Random Forest Model
  • eval : Juypter notebook contains the evaulation of the KGE models

The data provided

  • bank.csv and Telco_customer_churn.csv contains the orginal data
  • bank_prepped.csv and Telco_prepped.csv contain the data after balancing the classes and preperation
  • BankTriples.csv and TelcoTriples.csv contain the Knowldege Graph created from the above data

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Project on the use of Knowledge Graph Embeddings for use for a classification problem for Capstone Project submitted for the MSc of Data Analytics

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