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Pruning strategies for nearest neighbor competence preservation learners
Neurocomputing, 2018Abstract In order to alleviate both the spatial and temporal cost of the nearest neighbor classification rule, competence preservation techniques aim at substituting the training set with a selected subset, known as consistent subset. In order to improve generalization and to prevent induction of overly complex models, in this study the application ...
Fabrizio Angiulli, Estela Narvaez
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Diversity-aware strategies for static index pruning
Information Processing & ManagementStatic 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 +2 more
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A Dynamic Pruning Strategy for Incremental Learning on a Budget
2014Several 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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Pruning strategies for mining high utility itemsets
Expert Systems with Applications, 2015Presents 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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A ranking-based strategy to prune variable selection ensembles
Knowledge-Based Systems, 2017Ensemble 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 +2 more
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The Biases of Decision Tree Pruning Strategies
1999Post 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 Statistical Pruning Strategy for Schnorr-Euchner Sphere Decoding
IEEE Communications Letters, 2008The high computational complexity of maximum likelihood (ML) decoding can impact many applications such as code division multiple access (CDMA) and multiple-input multiple-output (MIMO) systems. The sphere decoder (SD) as an efficient ML decoder has therefore received significant attention in the wireless research community.
Alireza Ghaderipoor, Chintha Tellambura
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A comparative analysis of pruning strategies for fuzzy decision trees
2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013Decision 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 +2 more
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Unsupervised Synaptic Pruning Strategies for Restricted Boltzmann Machines
2018 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2018While 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 +4 more
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Mining Association Rules Based on Deep Pruning Strategies
Wireless Personal Communications, 2017Today 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 +4 more
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