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ChurnAnalysis

Customer Churn Analysis Experiments using Classical ML algorithms and Deep Neural Network

Install / Use

/learn @denopas/ChurnAnalysis
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

ChurnAnalysis

Customer Churn Analysis experiments are employed using Classical ML (Machine Learning) algorithms and Deep Neural Network (DNN). A dataset from telecom is used for experimental studies.

  1. Dataset is created in telecom domain.

  2. Classical Machine Learning Models:

  • Logistic Regression
  • Naive Bayes
  • Decision Tree (CART)
  • K-NN
  • SVM
  • LDA
  • AdaBoostClassifier
  • BaggingClassifier
  • RandomForestClassifier
  1. Deep Neural Network model is constructed based on Keras.

Related Skills

View on GitHub
GitHub Stars15
CategoryDevelopment
Updated2y ago
Forks14

Security Score

60/100

Audited on Jul 10, 2023

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