An effective strategy for churn prediction and customer profiling

Deep Learning for Anomaly Detection

(2021) Guansong Pang et al.   ACM COMPUTING SURVEYS

Semi-supervised anomaly detection algorithms: A comparative summary and future research directions

(2021) Miryam Elizabeth Villa-Pérez et al.   KNOWLEDGE-BASED SYSTEMS

GEV-NN: A deep neural network architecture for class imbalance problem in binary classification

(2020) Lkhagvadorj Munkhdalai et al.   KNOWLEDGE-BASED SYSTEMS

One-class support vector classifiers: A survey

(2020) Shamshe Alam et al.   KNOWLEDGE-BASED SYSTEMS

Spectral clustering via ensemble deep autoencoder learning (SC-EDAE)

(2020) Séverine Affeldt et al.   PATTERN RECOGNITION

Anomaly Detection Methods for Categorical Data

(2019) Ayman Taha et al.   ACM COMPUTING SURVEYS

A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees

(2018) Arno De Caigny et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Time series for early churn detection: Using similarity based classification for dynamic networks

(2018) María Óskarsdóttir et al.   EXPERT SYSTEMS WITH APPLICATIONS

Classifiers Combination Techniques: A Comprehensive Review

(2018) Mohamed Mohandes et al.   IEEE Access

Imbalance learning for the prediction of N6-Methylation sites in mRNAs

(2018) Zhixun Zhao et al.   BMC GENOMICS

An effective multivariate time series classification approach using echo state network and adaptive differential evolution algorithm

(2016) Lin Wang et al.   EXPERT SYSTEMS WITH APPLICATIONS

A comparison of machine learning techniques for customer churn prediction

(2015) T. Vafeiadis et al.   SIMULATION MODELLING PRACTICE AND THEORY

Improved churn prediction in telecommunication industry using data mining techniques

(2014) A. Keramati et al.   APPLIED SOFT COMPUTING

Assessing the impact of derived behavior information on customer attrition in the financial service industry

(2014) Leilei Tang et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

(2013) Victoria López et al.   INFORMATION SCIENCES

Improving customer retention in financial services using kinship network information

(2012) Dries F. Benoit et al.   EXPERT SYSTEMS WITH APPLICATIONS

Isolation-Based Anomaly Detection

(2012) Fei Tony Liu et al.   ACM Transactions on Knowledge Discovery from Data

On the effectiveness of preprocessing methods when dealing with different levels of class imbalance

(2011) V. García et al.   KNOWLEDGE-BASED SYSTEMS

Modelling and predicting customer churn from an insurance company

(2011) Clara-Cecilie Günther et al.   Scandinavian Actuarial Journal

Employee churn prediction

(2010) V. Vijaya Saradhi et al.   EXPERT SYSTEMS WITH APPLICATIONS

Combining discrete SVM and fixed cardinality warping distances for multivariate time series classification

(2010) C. Orsenigo et al.   PATTERN RECOGNITION

Anomaly detection

(2009) Varun Chandola et al.   ACM COMPUTING SURVEYS

Improved marketing decision making in a customer churn prediction context using generalized additive models

(2009) Kristof Coussement et al.   EXPERT SYSTEMS WITH APPLICATIONS

Handling class imbalance in customer churn prediction

(2008) J. Burez et al.   EXPERT SYSTEMS WITH APPLICATIONS

Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data

(2007) Mónica Bécue-Bertaut et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer

(2007) C CHAN   EXPERT SYSTEMS WITH APPLICATIONS

Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques

(2006) Kristof Coussement et al.   EXPERT SYSTEMS WITH APPLICATIONS