Results 1  10
of
6,536
Mining Association Rules with Multiple Minimum Supports
 In Knowledge Discovery and Data Mining
, 1999
"... Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a rul ..."
Abstract

Cited by 160 (7 self)
 Add to MetaCart
Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a
Minimum energy mobile wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1999
"... We describe a distributed positionbased network protocol optimized for minimum energy consumption in mobile wireless networks that support peertopeer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each n ..."
Abstract

Cited by 749 (0 self)
 Add to MetaCart
We describe a distributed positionbased network protocol optimized for minimum energy consumption in mobile wireless networks that support peertopeer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each
MinimumSupport Solutions for Radiotherapy Planning
"... This paper is concerned with nding solutions to the Radiotherapy Planning Problem (RTPP) that involve the fewest number of gantry angles possible. Such solutions are called minimum{support solutions. To address this issue we will modify a linear programming model from [8] by introducing a term into ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
This paper is concerned with nding solutions to the Radiotherapy Planning Problem (RTPP) that involve the fewest number of gantry angles possible. Such solutions are called minimum{support solutions. To address this issue we will modify a linear programming model from [8] by introducing a term
Integrating classification and association rule mining
 In Proc of KDD
, 1998
"... Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target of di ..."
Abstract

Cited by 578 (21 self)
 Add to MetaCart
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target
Mining Sequential patterns with Multiple Minimum Supports
, 2003
"... Sequential mining is becoming more and more important recently. Traditional sequential pattern mining algorithms used the same model, i.e., finding all sequential patterns that satisfy one userspecified minimum support. However, using only one single minimum support implies that all items in the da ..."
Abstract
 Add to MetaCart
Sequential mining is becoming more and more important recently. Traditional sequential pattern mining algorithms used the same model, i.e., finding all sequential patterns that satisfy one userspecified minimum support. However, using only one single minimum support implies that all items
Mining Sequential Patterns: Generalizations and Performance Improvements
 RESEARCH REPORT RJ 9994, IBM ALMADEN RESEARCH
, 1995
"... The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transactiontime, and each transaction is a set of items. The problem is to discover all sequential patterns with a userspecified ..."
Abstract

Cited by 759 (5 self)
 Add to MetaCart
specified minimum support, where the support of a pattern is the number of datasequences that contain the pattern. An example of a sequential pattern is "5 % of customers bought `Foundation' and `Ringworld' in one transaction, followed by `Second Foundation ' in a later transaction". We
Tight frames with maximum vanishing moments and minimum support
 In Approximation theory, X
, 2002
"... Abstract. The introduction of vanishing moment recovery (VMR) functions in our recent work (also called “fundamental functions ” in an independent paper by Daubechies, Han, Ron, and Shen) modifies the socalled “unitary extension principle ” to allow the construction of compactly supported affine fr ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
on the investigation of tight frame generators with minimum supports. In particular, a computational scheme to be described as an algorithm is developed for constructing such minimumsupported tight frame generators. An example is included as an illustration of this algorithm. The parametric representation of curves
Mining Association Rules with Multiple Minimum Supports
"... Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a rul ..."
Abstract
 Add to MetaCart
Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a
Mining Association Rules with Multiple Minimum Supports
"... Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a rul ..."
Abstract
 Add to MetaCart
Association rule mining is an important model in data mining. Its mining algorithms discover all item associations (or rules) in the data that satisfy the userspecified minimum support (minsup) and minimum confidence (minconf) constraints. Minsup controls the minimum number of data cases that a
MinimumSupport Solutions of Polyhedral Concave Programs
 OPTIMIZATION
, 1999
"... Motivated by the successful application of mathematical programming techniques to difficult machine learning problems, we seek solutions of concave minimization problems over polyhedral sets with a minimum number of nonzero components. We prove that if such problems have a solution, they have a v ..."
Abstract

Cited by 16 (2 self)
 Add to MetaCart
vertex solution with a minimal number of zeros. This includes linear programs and general linear complementarity problems. A smooth concave exponential approximation to a step function solves the minimumsupport problem exactly for a finite value of the smoothing parameter. A fast finite linear
Results 1  10
of
6,536