Results 31 to 40 of about 9,278,183 (294)
Evolving temporal association rules with genetic algorithms [PDF]
, 2010 A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant - temporal ...
Gongora, Mario A. +6 more
core +1 more source
Secure Association Rule Sharing [PDF]
, 2004 The sharing of association rules is often beneficial in industry, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal strategic patterns which we call restrictive rules. These restrictive rules must be protected before sharing since they are paramount for strategic decisions and need to remain private.
Oliveira, Stanley R. M. +2 more
openaire +4 more sources
NiaAutoARM: Automated Framework for Constructing and Evaluating Association Rule Mining Pipelines
MathematicsNumerical Association Rule Mining (NARM), which simultaneously handles both numerical and categorical attributes, is a powerful approach for uncovering meaningful associations in heterogeneous datasets.
Uroš Mlakar, Iztok Fister, Iztok Fister
doaj +1 more source
An Adaptive Approach to Quantify Plant Features by Using Association Rule-Based Similarity
IEEE Access, 2019 In elementary school, the first step to learning about plants is observing plant features. In this study, we developed a plant search system that allows users to do a search even when they do not know the plant name simply by observing plant ...
Shu-Chen Cheng, Yu-Ping Cheng
doaj +1 more source
, 2020 Two-process theories of human cognition, that state that learning can occur by both associative and rule-based processes, are currently popular. We report two experiments which support such a view. Both employed a set of six stimuli which varied along a luminance dimension, and followed the same general design.
Jones, F. W., McLaren, I. P. L.
openaire +1 more source
Looking at the class associative classification training algorithm [PDF]
, 2007 Associative classification (AC) is a branch in data mining that utilises association rule discovery methods in classification problems. In this paper, we propose a new training method called Looking at the Class (LC), which can be adapted by any rule ...
McCluskey, T.L. +2 more
core +5 more sources
New Associative Classification Method Based on Rule Pruning for Classification of Datasets
IEEE Access, 2019 In data mining, a rule-based classification approach called Associative Classification (AC) normally builds accurate classifiers from supervised learning data sets. It extracts “If-Then” rules and associates each of the generated rules with
Khairan D. Rajab
doaj +1 more source
Frontiers in Environmental Science, 2022 The imbalance of socioeconomic development (SED) in different regions of China has resulted in the variability of rural infrastructure penetration. This study aims to improve the SED of each region in China to increase the penetration rate of rural ...
Yong Li +8 more
doaj +1 more source
Solid Pseudopapillary Neoplasm of the Pancreas in Children and Adolescents: Expert Recommendations
Pediatric Blood &Cancer, EarlyView.ABSTRACT Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare low‐grade malignant exocrine pancreatic tumor, mostly discovered during the second decade of life in females, with a very good prognosis, provided microscopically complete surgical excision is achieved.
Sabine Irtan +18 more
wiley +1 more source
IEEE Open Journal of the Computer SocietySoftware defect prediction (SDP) optimizes testing resource allocation by enabling timely detection of potential defects. Association rule mining, a highly interpretable and high-performance data mining technique, has proven effective as an SDP predictor.
Wentao Wu +8 more
doaj +1 more source