predicting churn in telco industry: machine learning approach - marko mitić
TRANSCRIPT
Dr. Marko MitićBusiness Data Analyst at Telenor Serbia
Predicting churn in telco industry: machine learning approach
Contents• Introduction to machine learning
• Churn definition & telco data
• Algorithm description
• Data exploration
• Modelling in R language
• Conclusion
Introduction to machine learningSupervised learningEach training example is a pair consisting of an input object and a desired output value
• Regression (real values)• Classification (discrete labels)
Unsupervised learningDraw inferences from datasets data without labeled responses
• Clustering• Dimensionality reduction
Reinforcement learningAgents ought to take actions in an environment so as to maximize cumulative reward
Introduction to machine learning
Regression Classification
Clustering ReinforcementLearning
Introduction to machine learning
Training set (observed)
Universal set(unobserved)
Testing set(unobserved)
Data acquisition
Practical usage
Classification
Churn definitionChurn rate (sometimes called attrition rate), is a measure of the number of individuals or items moving out of a collective group over a specific period of time
= Customer leaving
Pay TVE-mail/website subscribersLegal sectorRecreation Newspaper subscribers
Telco dataReal telco data available in latest C50 library in R language
Feature engineering: 3/6 months average usage, average total charge,...
Algorithms1. Logistic Regression• In logistic regression the outcome variable is binary, and the
purpose of the analysis is to assess the effects of multiple explanatory variables
Odds of success = P / 1-P = = e α + β1X1 + β2X2 + …+βpXp
The joint effects of all explanatory variables put together on the odds isLogit P = α+β1X1+β2X2+..+βpXp
Algorithms2. Support Vector Machines• SVMs maximize the margin around the
separating hyperplane.• The decision function is fully specified by a
subset of training samples, the support vectors.wTxi + b ≥ 1, if yi = 1wTxi + b ≤ −1, if yi = −1
w2ρ• Margin
Algorithms3. Neural Network
• A neuron network (NN) is a computational model based on the structure and functions of biological neural networks.
• A neural network usually involves a large number of processing units with the aim of successfully mapping input to output space through iterative process
Conclusions• 3 machine algorithms for churn prediction are presented
• Logistic Regression and BP Neural Net with boosting gave best results
• Good base for successfull broadcast campaign towards potential churners
Works even better• Implementation of more complex ML algorithms (Random Forest,
Gradient Boosting Machines, Deep NNs)
• Generate hybrid ensemble models
