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Results 1 - 10
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150
Correlation-based feature selection for machine learning
, 1998
"... A central problem in machine learning is identifying a representative set of features from which to construct a classification model for a particular task. This thesis addresses the problem of feature selection for machine learning through a correlation based approach. The central hypothesis is that ..."
Abstract
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Cited by 318 (3 self)
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this evaluation formula with an appropriate correlation measure and a heuristic search strategy. CFS was evaluated by experiments on artificial and natural datasets. Three machine learning algorithms were used: C4.5 (a decision tree learner), IB1 (an instance based learner), and naive Bayes. Experiments
Eliminating Noisy Information in Web Pages for Data Mining
- In ACM Conf. on Knowledge Discovery and Data Mining (SIGKDD
, 2003
"... A commercial Web page typically contains many information blocks. Apart from the main content blocks, it usually has such blocks as navigation panels, copyright and privacy notices, and advertisements (for business purposes and for easy user access). We call these blocks that are not the main co ..."
Abstract
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Cited by 108 (2 self)
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Web site, noisy blocks usually share some common contents and presentation styles, while the main content blocks of the pages are often diverse in their actual contents and/or presentation styles. Based on this observation, we propose a tree structure, called Style Tree, to capture the common
GRAPH SEARCHING WITH ADVICE
, 2007
"... Fraigniaud et al. (2006) introduced a new measure of difficulty for a distributed task in a network. The smallest number of bits of advice of a distributed problem is the smallest number of bits of information that has to be available to nodes in order to accomplish the task efficiently. Our paper ..."
Abstract
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Cited by 13 (5 self)
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and arbitrarily fast fugitive in a monotone connected way, i.e., the cleared part of the graph is permanently connected, and never decreases while the search strategy is executed. We show that the minimum number of bits of advice permitting the monotone connected clearing of a network in a distributed setting
Tree Exploration with Advice
, 2008
"... We study the amount of knowledge about the network that is required in order to efficiently solve a task concerning this network. The impact of available information on the efficiency of solving network problems, such as communication or exploration, has been investigated before but assumptions conc ..."
Abstract
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Cited by 6 (5 self)
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concerned availability of particular items of information about the network, such as the size, the diameter, or a map of the network. In contrast, our approach is quantitative: we investigate the minimum number of bits of information (bits of advice) that has to be given to an algorithm in order to perform
Management advice from tree measurements
, 1999
"... Introduction The u timate objective of permanent p ots and growt h mode s is to provide management advice. We are often too pre-occupied with getting the data and bui ding the mode to think too much about providing practica management advice. But it is an important issue that shou d not be neg ec ..."
Abstract
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ected, or postponed unti the mode is finished, because it shou d have an inf uence on mode design and imp ementation. So, how do we turn tree measurements into management advice? Do you know the word game where you turn one word into another by changing one etter at a time (and if necessary, shuff
Layered Learning in Multi-Agent Systems
, 1998
"... search, or the U.S. Government. Keywords: Multi-agent systems, machine learning, multi-agent learning, control learning, hierarchical learning, reinforcement learning, decision tree learning, neural networks, robotic soccer, network routing Multi-agent systems in complex, real-time domains require a ..."
Abstract
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Cited by 134 (11 self)
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search, or the U.S. Government. Keywords: Multi-agent systems, machine learning, multi-agent learning, control learning, hierarchical learning, reinforcement learning, decision tree learning, neural networks, robotic soccer, network routing Multi-agent systems in complex, real-time domains require
Permanent Member
, 2006
"... Two-player complete-information game trees are perhaps the simplest possible setting for studying general-sum games and the computational problem of finding equilibria. These games admit a simple bottom-up algorithm for finding subgame perfect Nash equilibria efficiently. However, such an algorithm ..."
Abstract
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stochastic decisions and demonstrate Game-tree search for zero-sum games has been a staple of AI research since its earliest days. Recently, research on general-sum games has intensified as a way of reasoning about more complex agent interactions (Kearns et al. 2001). In this paper, we treat the problem of
Analyzing Evolutionary Optimization in Noisy Environments
"... Many optimization tasks must be handled in noisy environments, where the exact evaluation of a solution cannot be obtained, only a noisy one. For optimization of noisy tasks, evolutionary algorithms (EAs), a type of stochastic metaheuristic search algorithm, have been widely and successfully applied ..."
Abstract
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Many optimization tasks must be handled in noisy environments, where the exact evaluation of a solution cannot be obtained, only a noisy one. For optimization of noisy tasks, evolutionary algorithms (EAs), a type of stochastic metaheuristic search algorithm, have been widely and successfully
A Theory of Learning Classification Rules
, 1992
"... The main contributions of this thesis are a Bayesian theory of learning classification rules, the unification and comparison of this theory with some previous theories of learning, and two extensive applications of the theory to the problems of learning class probability trees and bounding error whe ..."
Abstract
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Cited by 89 (6 self)
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The main contributions of this thesis are a Bayesian theory of learning classification rules, the unification and comparison of this theory with some previous theories of learning, and two extensive applications of the theory to the problems of learning class probability trees and bounding error
Variable KD-Tree Algorithms for Efficient Spatial Pattern Search
, 2005
"... In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of efficiently linking faint asteroid detections, but is applicable to a range of spatial queries. We survey ..."
Abstract
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Cited by 2 (0 self)
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In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of efficiently linking faint asteroid detections, but is applicable to a range of spatial queries. We survey
Results 1 - 10
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150
