Buscar
Mostrando ítems 1-10 de 147
Characterizing Efficiency on Infinite-dimensional Commodity Spaces with Ordering Cones Having Possibly Empty Interior
(Springer, 2015)
Some production models in finance require infinite-dimensional commodity
spaces, where efficiency is defined in terms of an ordering cone having possibly
empty interior. Since weak efficiency is more tractable than ...
Profit-based churn prediction based on Minimax Probability Machines
(Elsevier, 2020)
In this paper, we propose three novel profit-driven strategies for churn prediction. Our proposals extend the ideas of the Minimax Probability Machine, a robust optimization approach for binary classification that maximizes ...
Automatic Feature Scaling and Selection for Support Vector Machine Classi cation with Functional Data
(Springer, 2020)
Functional Data Analysis (FDA) has become a very important eld
in recent years due to its wide range of applications. However, there are several
real-life applications in which hybrid functional data appear, i.e., data ...
Dynamic Rough-Fuzzy Support Vector Clustering
(IEEE, 2017)
Clustering is one of the main data mining tasks with many proven techniques and successful real-world applications. However, in changing environments, the existing systems need to be regularly updated in order to describe ...
Learning in Combinatorial Optimization: What and How to Explore
(INFORMS, 2020)
We study dynamic decision making under uncertainty when, at each period, a decision maker implements a solution to a combinatorial optimization problem. The objective coefficient vectors of said problem, which are unobserved ...
Simultaneous preference estimation and heterogeneity control for choice-based conjoint via support vector machines
(Palgrave Macmillan Ltd., 2017)
Support vector machines (SVMs) have been successfully used to identify individuals' preferences in conjoint analysis. One of the challenges of using SVMs in this context is to properly control for preference heterogeneity ...
Profit-based feature selection using support vector machines - General framework and an application for customer retention
(Elsevier, 2015)
Churn prediction is an important application of classification models that identify those customers most likely to attrite based on their respective characteristics described by e.g. socio-demographic and behavioral ...
Average Binary Long-Lived Consensus: Quantifying the Stabilizing Role Played by Memory
(2009)
Consider a system composed of n sensors operating in synchronous
rounds. In each round an input vector of sensor readings x is
produced, where the i-th entry of x is a binary value produced by the
i-th sensor. The ...
Feature selection for Support Vector Machines via Mixed Integer Linear Programming
(Elsevier, 2014)
The performance of classification methods, such as Support Vector Machines, depends
heavily on the proper choice of the feature set used to construct the classifier. Feature
selection is an NP-hard problem that has been ...
Non stationary demand forecasting based on empirical mode decomposition and support vector machines
(IEEE, 2017)
A company performance strongly depends on its ability of delivering the right quantity of of a given product at the time customers require. Even though some demand forecasting techniques have been developed, they have ...