Results 211 to 220 of about 28,526 (253)
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Applied Intelligence, 1998
Feature selection is a problem of finding relevant features. When the number of features of a dataset is large and its number of patterns is huge, an effective method of feature selection can help in dimensionality reduction. An incremental probabilistic algorithm is designed and implemented as an alternative to the exhaustive and heuristic approaches.
Liu, H., Setiono, R.
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Feature selection is a problem of finding relevant features. When the number of features of a dataset is large and its number of patterns is huge, an effective method of feature selection can help in dimensionality reduction. An incremental probabilistic algorithm is designed and implemented as an alternative to the exhaustive and heuristic approaches.
Liu, H., Setiono, R.
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Incremental feature weighting for fuzzy feature selection
Fuzzy Sets and Systems, 2019Abstract Feature selection presents many challenges and difficulties during online learning. In this study, we focus on fuzzy feature selection for fuzzy data stream. We present a novel incremental feature weighting method with two main phases comprising offline fuzzy feature selection and online fuzzy feature selection.
Ling Wang 0014 +4 more
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Rough Set Theory Based Group Incremental Approach to Feature Selection
Information Sciences, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jie Zhao 0011 +5 more
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Incremental approaches for heterogeneous feature selection in dynamic ordered data
Information Sciences, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Binbin Sang +4 more
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Incremental Bayesian Network Learning for Scalable Feature Selection
2009Our aim is to solve the feature subset selection problem with thousands of variables using an incremental procedure. The procedure combines incrementally the outputs of non-scalable search-and-score Bayesian network structure learning methods that are run on much smaller sets of variables. We assess the scalability, the performance and the stability of
Grégory Thibault +2 more
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Immune-inspired incremental feature selection technology to data streams
Applied Soft Computing, 2008As data streams are gaining prominence in a growing number of emerging applications, advanced analysis and mining of data streams is becoming increasingly important. In this paper, an immune-inspired incremental feature selection algorithm called ISFaiNET is proposed as a solution for mining data streams, immune network memory antibody set which is far
Xun Yue, Hongwei Mo, Zhong-Xian Chi
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Incremental feature selection for efficient classification of dynamic graph bags
Concurrency and Computation: Practice and Experience, 2019SummaryLearning and analyzing graph data is one of the most fundamental research areas in machine learning and data mining. Among numerous graph‐based data structures, this paper focuses on a graph bag (simply, bag), which corresponds to a training object containing one or more graphs, and a label is available only for a bag.
Dong-Kyu Chae +3 more
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An Incremental Algorithm to Feature Selection in Decision Systems with the Variation of Feature Set
Chinese Journal of Electronics, 2015Feature selection is a challenging problem in pattern recognition and machine learning. In real-life applications, feature set in the decision systems may vary over time. There are few studies on feature selection with the variation of feature set. This paper focuses on this issue, an incremental feature selection algorithm in dynamic decision systems ...
Wenbin Qian +3 more
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On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams
2005In this paper we argue that incrementally updating the features that a text classification algorithm considers is very important for real-world textual data streams, because in most applications the distribution of data and the description of the classification concept changes over time.
Ioannis Katakis 0001 +2 more
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A group incremental approach for feature selection on hybrid data
Soft Computing, 2022Feng Wang 0038, Wei Wei 0018, Jiye Liang
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