The assessment of knowledge derived from databases depends on many factors. Decision makers often need to convince others about the correctness and effectiveness of knowledge induced from data.The current data mining techniques do not contribute much to this process of persuasion.Part of this limitation can be removed by integrating knowledge from experts in the field, encoded in some accessible way, with knowledge derived form patterns stored in the database.In this paper we will in particular discuss methods for implementing monotonicity constraints in economic decision problems.This prior knowledge is combined with data mining algorithms based on decision trees and neural networks.The method is illustrated in a hedonic price model
One of the most important problems in modern finance is finding efficient ways to summarize and visu...
Abstract. We propose a novel approach to discover useful patterns from ill-defined decision tables w...
In recent years, researchers in the Field of Artificial Intelligence have developed a learning techn...
The objective of data mining is the extraction of knowledge from databases. In practice, one often e...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
Data Mining represents the extraction previously unknown, and potentially useful information from da...
Data mining is a process of finding hidden regularities and connections among data. Base data mining...
This thesis describes a number of new data mining algorithms which were the result of our research i...
Along with the increase of economic globalization and the evolution of information technology, data ...
Abstract: Market basket analysis is one of the typical applications in mining association rules. The...
In this paper, we develop a decision-theoretic framework for evaluating data mining systems, which e...
Feed forward neural networks receive a growing attention as a data modelling tool in economic classi...
This paper describes the use of decision tree and rule induction in data mining applications. Of met...
Companies' interest in customer relationship modelling and key issues such as customer lifetime valu...
Growing popularity of the Internet and innovative storage technology have caused a true data explosi...
One of the most important problems in modern finance is finding efficient ways to summarize and visu...
Abstract. We propose a novel approach to discover useful patterns from ill-defined decision tables w...
In recent years, researchers in the Field of Artificial Intelligence have developed a learning techn...
The objective of data mining is the extraction of knowledge from databases. In practice, one often e...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
Data Mining represents the extraction previously unknown, and potentially useful information from da...
Data mining is a process of finding hidden regularities and connections among data. Base data mining...
This thesis describes a number of new data mining algorithms which were the result of our research i...
Along with the increase of economic globalization and the evolution of information technology, data ...
Abstract: Market basket analysis is one of the typical applications in mining association rules. The...
In this paper, we develop a decision-theoretic framework for evaluating data mining systems, which e...
Feed forward neural networks receive a growing attention as a data modelling tool in economic classi...
This paper describes the use of decision tree and rule induction in data mining applications. Of met...
Companies' interest in customer relationship modelling and key issues such as customer lifetime valu...
Growing popularity of the Internet and innovative storage technology have caused a true data explosi...
One of the most important problems in modern finance is finding efficient ways to summarize and visu...
Abstract. We propose a novel approach to discover useful patterns from ill-defined decision tables w...
In recent years, researchers in the Field of Artificial Intelligence have developed a learning techn...