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Response modeling with support vector regression
10 references·6 citing·43 second hop
Response modeling with support vector regression (2006)Response modeling with support vector reg…Response models based on bagging neural networks (2005)Response models based on bagg…Response modeling with support vector machines (2005)Response modeling with suppor…Mining Customer Value: From Association Rules to Direct Marketing (2005)Mining Customer Value: From A…Knowledge discovery in a direct marketing case using least squares support vector machines (2001)Knowledge discovery in a dire…Neural networks and the multinomial logit for brand choice modelling: a hybrid approach (2000)Neural networks and the multi…Mailing smarter to catalog customers (2000)Mailing smarter to catalog cu…Customer list segmentation using the combined response model (1999)Customer list segmentation us…Data mining for direct marketing: problems and solutions (1998)Data mining for direct market…Direct marketing modeling with CART and CHAID (1997)Direct marketing modeling wit…Applying neural computing to target marketing (1997)Applying neural computing to …Class balancing in customer segments classification using support vector machine rule extraction and ensemble learning (2020)Class balancing in customer s…Customer Value Prediction in Direct Marketing Using Hybrid Support Vector Machine Rule Extraction Method (2019)Customer Value Prediction in …Including spatial interdependence in customer acquisition models: A cross-category comparison (2012)Including spatial interdepend…Optimal selection of potential customer range through the union sequential pattern by using a response model (2010)Optimal selection of potentia…Semi-Supervised Response Modeling (2009)Semi-Supervised Response Mode…Data augmentation by predicting spending pleasure using commercially available external data (2009)Data augmentation by predicti…Conditional logit analysis of qualitative choice behavior (1972)A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Discrete Choice Analysis (1985)The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis (2015)Video mining: Measuring visual information using automatic methods (2019)Enhancing discrete choice models with representation learning (2020)An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data (1993)Constrained optimization of data-mining problems to improve model performance: A direct-marketing application (2005)Constructing a reassigning credit scoring model (2007)Facilitating cross-selling in a mobile telecom market to develop customer classification model based on hybrid data mining techniques (2010)Discrete Choice Analysis (2014)Dummy Endogenous Variables in a Simultaneous Equation System (1977)A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data (1984)A Probabilistic Choice Model for Market Segmentation and Elasticity Structure (1989)A Hidden Markov Model of Customer Relationship Dynamics (2005)Reward redemption effects in a loyalty program when customers choose how much and when to redeem (2014)LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning (2020)Marketing Research (1970)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A stochastic RFM model (1999)Staying Power of Churn Prediction Models (2010)Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework (2013)The theory and practice of econometrics (1986)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Bankruptcy prediction using neural networks (1994)The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands (2003)A dynamic segmentation approach for targeting and customizing direct marketing campaigns (2006)Successful direct marketing methods (1975)Mailing Decisions in the Catalog Sales Industry (1996)Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models (1998)DEVELOPING A SHORT AFFECT INTENSITY SCALE (2002)Targeting direct marketing campaigns by neural networks (2011)Optimal Selection for Direct Mail (1995)Extracting Actionable Knowledge from Decision Trees (2006)Extracting Actionable Knowledge from Decision Trees (2007)Customer Churn Prediction in Telecommunication A Decade Review and Classification (2013)Handling class imbalance in customer churn prediction (2008)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Credit Risk Analysis Using Machine and Deep Learning Models (2018)Market segmentation by tourists’ sentiments (2003)Negative emotions and their effect on customer complaint behaviour (2011)Customer event history for churn prediction: How long is long enough? (2012)Response Modeling in Direct Marketing (2013)
this work references cited by second hop

References

  • 1998Data mining for direct marketing: problems and solutions658 cited
  • 1997Applying neural computing to target marketing125 cited
  • 1997Direct marketing modeling with CART and CHAID124 cited
  • 2000Neural networks and the multinomial logit for brand choice modelling: a hybrid approach123 cited
  • 2005Mining Customer Value: From Association Rules to Direct Marketing114 cited
  • 2005Response models based on bagging neural networks107 cited
  • 2000Mailing smarter to catalog customers92 cited
  • 2005Response modeling with support vector machines92 cited
  • 2001Knowledge discovery in a direct marketing case using least squares support vector machines79 cited
  • 1999Customer list segmentation using the combined response model69 cited

Cited by

  • 2009Data augmentation by predicting spending pleasure using commercially available external data38 cited
  • 2009Semi-Supervised Response Modeling25 cited
  • 2010Optimal selection of potential customer range through the union sequential pattern by using a response model18 cited
  • 2020Class balancing in customer segments classification using support vector machine rule extraction and ensemble learning15 cited
  • 2012

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Including spatial interdependence in customer acquisition models: A cross-category comparison
14 cited
  • 2019Customer Value Prediction in Direct Marketing Using Hybrid Support Vector Machine Rule Extraction Method10 cited