Michel Ballings
Michel Ballings
The University of Tennessee, department of Business Analytics and Statistics
Verified email at utk.edu - Homepage
TitleCited byYear
Evaluating multiple classifiers for stock price direction prediction
M Ballings, D Van den Poel, N Hespeels, R Gryp
Expert Systems with Applications 42 (20), 7046-7056, 2015
1802015
Customer Event History for Churn Prediction: How long is long enough?
M Ballings, DV Poel
Expert Systems with Applications, 2012
602012
CRM in social media: Predicting increases in Facebook usage frequency
M Ballings, D Van den Poel
European Journal of Operational Research 244 (1), 248-260, 2015
492015
Identifying new product ideas: waiting for the wisdom of the crowd or screening ideas in real time
S Hoornaert, M Ballings, EC Malthouse, D Van den Poel
Journal of Product Innovation Management 34 (5), 580-597, 2017
392017
AUC: threshold independent performance measures for probabilistic classifiers. 2013
M Ballings, D Van den Poel
URL http://CRAN. R-project. org/package= AUC. R package version 0.3. 0, 2017
31*2017
The added value of auxiliary data in sentiment analysis of Facebook posts
M Meire, M Ballings, D Van den Poel
Decision Support Systems 89, 98-112, 2016
312016
Social media optimization: Identifying an optimal strategy for increasing network size on Facebook
M Ballings, D Van den Poel, M Bogaert
Omega 59, 15-25, 2016
242016
Kernel Factory: An ensemble of kernel machines
M Ballings, D Van den Poel
Expert Systems with Applications 40 (8), 2904-2913, 2013
222013
The added value of Facebook friends data in event attendance prediction
M Bogaert, M Ballings, D Van den Poel
Decision Support Systems 82, 26-34, 2016
182016
The added value of social media data in B2B customer acquisition systems: A real-life experiment
M Meire, M Ballings, D Van den Poel
Decision Support Systems 104, 26-37, 2017
152017
Cause marketing and customer profitability
M Ballings, H McCullough, N Bharadwaj
Journal of the Academy of Marketing Science 46 (2), 234-251, 2018
132018
Evaluating the importance of different communication types in romantic tie prediction on social media
M Bogaert, M Ballings, D Van den Poel
Annals of Operations Research 263 (1-2), 501-527, 2018
112018
Improving customer churn prediction by data augmentation using pictorial stimulus-choice data
M Ballings, D Van den Poel, E Verhagen
Management intelligent systems, 217-226, 2012
52012
Identifying soccer players on Facebook through predictive analytics
M Bogaert, M Ballings, M Hosten, D Van den Poel
Decision Analysis 14 (4), 274-297, 2017
42017
Using Eye-Tracking Data of Advertisement Viewing Behavior to Predict Customer Churn
M Ballings, D Van den Poel
2013 IEEE 13th International Conference on Data Mining Workshops, 201-205, 2013
22013
RFM Variables Revisited Using Quantile Regression
M Ballings, D Benoit, D Van den Poel
2011 11th IEEE International Conference on Data Mining Workshops, 1163-1169, 2011
22011
The Role of Marketer-Generated Content in Customer Engagement Marketing
M Meire, K Hewett, M Ballings, V Kumar, D Van den Poel
Journal of Marketing 83 (6), 21-42, 2019
12019
Equity price direction prediction for day trading: Ensemble classification using technical analysis indicators with interaction effects
D Van den Poel, C Chesterman, M Koppen, M Ballings
2016 IEEE Congress on Evolutionary Computation (CEC), 3455-3462, 2016
12016
rotationForest: Fit and Deploy Rotation Forest Models
M Ballings, D Van den Poel
http://cran.r-project.org/web/packages/rotationForest/index.html, 2015
12015
Advances and applications in Ensemble Learning
M Ballings
Ghent University, 2014
12014
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