Results 261 to 270 of about 31,077 (302)

A comparative analysis of pruning strategies for fuzzy decision trees

2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013
Decision trees are powerful models which can be applied to classification tasks. Fuzzy decision trees unite the advantages of the classic decision trees, which produce simple models with high interpretability, competitive accuracy, and a graphical representation, as well as the advantages of fuzzy systems, which include the capability of dealing with ...
Mariana V. Ribeiro, Heloisa A. Camargo, Marcos E. Cintra   +2 more
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A Novel Pruning Strategy for Mining Discriminative Patterns

Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2021
Discriminative patterns are sets of characteristics that differentiate multiple groups from each other, for example, successful and unsuccessful medical treatments. The objective of the discriminative pattern mining task is to discover a set of significant patterns that occur with disproportionate frequencies in different class-labeled datasets ...
Nader Aryabarzan, Behrouz Minaei-Bidgoli
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Unsupervised Synaptic Pruning Strategies for Restricted Boltzmann Machines

2018 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2018
While unsupervised generative neural networks are attractive choices for adoption in always-on continuous-time smart sensory systems, they typically impose heavy memory requirements on the underlying computational fabric. Recent literature on binarized neural networks has not yet been extended to unsupervised generative networks and alternate ...
Surabhi Kalyan, Siddharth Joshi 0001, Sadique Sheik, Bruno U. Pedroni, Gert Cauwcnbcrghs   +4 more
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Diversity-aware strategies for static index pruning

Information Processing & Management
Static index pruning aims to remove redundant parts of an index to reduce the file size and query processing time. In this paper, we focus on the impact of index pruning on the topical diversity of query results obtained over these pruned indexes, due to the emergence of diversity as an important metric of quality in modern search systems.
Sevgi Yigit-Sert, Ismail Sengor Altingovde, Özgür Ulusoy   +2 more
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Mining Association Rules Based on Deep Pruning Strategies

Wireless Personal Communications, 2017
Today mobile network and various smart devices flourish rapidly. Data collected from the mobile devices and network can bring us huge opportunities to understand some significant characteristics of the users which traditional data cannot. Association rules mining is an extremely important topic in data mining that can make the utmost value of massive ...
Lei Li 0009, Qi Li 0057, Yabin Wu, Yihang Ou, Daoxin Chen   +4 more
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Pruning strategies for mining high utility itemsets

Expert Systems with Applications, 2015
Presents an efficient high utility mining method.Employs novel pruning strategies to limit the search space of utility mining.Compares the proposed method against a state-of-the-art utility mining method.Experimentally evaluates the system on eight real and synthetic benchmark datasets.Empirical results are found to be quite promising, especially for ...
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High-Utility Itemset Mining with Effective Pruning Strategies

ACM Transactions on Knowledge Discovery from Data, 2019
High-utility itemset mining is a popular data mining problem that considers utility factors, such as quantity and unit profit of items besides frequency measure from the transactional database. It helps to find the most valuable and profitable products/items that are difficult to track by using only the frequent itemsets.
Jimmy Ming-Tai Wu, Jerry Chun-Wei Lin, Ashish Tamrakar   +2 more
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The Biases of Decision Tree Pruning Strategies

1999
Post pruning of decision trees has been a successful approach in many real-world experiments, but over all possible concepts it does not bring any inherent improvement to an algorithm's performance. This work explores how a PAC-proven decision tree learning algorithm fares in comparison with two variants of the normal top-down induction of decision ...
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A Dynamic Pruning Strategy for Incremental Learning on a Budget

2014
Several kernel-based perceptron learning methods on a budget have been proposed. In the early steps of learning, such methods record a new instance by allocating it a new kernel. In the later steps, however, useless memory must be forgotten to make space for recording important and new instances once the number of kernels reaches an upper bound.
Yusuke Kondo, Koichiro Yamauchi 0001
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A ranking-based strategy to prune variable selection ensembles

Knowledge-Based Systems, 2017
Ensemble pruning techniques are introduced in the context of variable selection.A ranking-based strategy is devised to prune a variable selection ensemble.The ensemble members are sorted by the prediction error of their associated models.Higher selection accuracy is gained by fusing fewer members ranked ahead.The superiority of the novel method over ...
Chun-Xia Zhang 0002, Jiang-She Zhang 0001, Qingyan Yin   +2 more
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