Ricardo Montoya

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T he U.S. pharmaceutical industry spent upwards of $18 billion on marketing drugs in 2005; detailing and drug sampling activities accounted for the bulk of this spending. To stay competitive, pharmaceutical managers need to maximize the return on these marketing investments by determining which physicians to target as well as when and how to target them. In(More)
We propose a linearly penalized support vector machines (LP-SVM) model for feature selection. Its application to a problem of customer retention and a comparison with other feature selection techniques underlines its effectiveness. 1 Introduction One of the tasks of Statistics and Data Mining consists of extracting patterns contained in large data bases. In(More)
BACKGROUND AND PURPOSE This study aimed to identify predictors of acute mortality after intracerebral hemorrhage (ICH), including voxel-wise analysis of hematoma location. METHODS In 282 consecutive patients with acute ICH, clinical and radiological predictors of acute mortality were identified. Voxel-based lesion-symptom mapping examined spatial(More)
To optimally allocate its marketing mix across customers, a firm needs to consider the evolution of its customers over time. Changes in the marketing environment, as well as intrinsic changes in preferences or needs, may discretely shift customers into different buying-behavior states. The ability to identify the dynamics in customer behavior and its(More)
One of the main tasks of Conjoint Analysis is to identify consumer preferences about potential products or services. Accordingly, different estimation methods have been proposed to determine the corresponding relevant attributes. Most of these approaches rely on the post-processing of the estimated preferences to establish the importance of such variables.(More)
This paper presents a novel embedded feature selection approach for Support Vector Machines (SVM) in a choice-based conjoint context. We extend the L1-SVM formulation and adapt the RFE-SVM algorithm to conjoint analysis to encourage sparsity in consumer preferences. This sparsity can be attributed to consumers being selective about the attributes they(More)
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