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A comparative analysis of meta-heuristic optimization algorithms for feature selection and feature weighting in neural networks
Feature selection and feature weighting are frequently used in machine learning for processing high dimensional data. It reduces the number of...
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SenticNet-Based Feature Weighting Scheme for Sentiment Classification
Sentiment analysis aims to study the peoples’ perceptions, sentiments and emotions in comments, blogs, review and so on. The performance of...
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Sparse robust multiview feature selection via adaptive-weighting strategy
Due to the rich and comprehensive information of multiview data, multi-view learning has been attracted widely attention. Efficiently exploiting...
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A feature weighted K-nearest neighbor algorithm based on association rules
K-nearest neighbors (kNN) is a popular machine learning algorithm because of its clarity, simplicity, and efficacy. kNN has numerous drawbacks,...
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Concept drift detection methods based on different weighting strategies
The distribution of data often evolves over time, necessitating classifiers to adjust in order to maintain optimal classification accuracy. This...
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An Evolving Feature Weighting Framework for Granular Fuzzy Logic Models
Discovering and extracting knowledge from large databases are key elements in granular computing (GrC). The knowledge extracted, in the form of...
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A Novel Training Approach in Deep Spiking Neural Network Based on Fuzzy Weighting and Meta-heuristic Algorithm
The challenge of supervised learning in spiking neural networks (SNNs) for digit classification from speech signals is examined in this study....
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A Content-Based Group Recommender System Using Feature Weighting and Virtual Users Aggregation
Recommender systems (RSs) are tools that help users to make decisions, when they face overloaded domains, suggesting the best items according to...
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Instructor-assisted question classification system using machine learning algorithms with N-gram and weighting schemes
One aspect of natural language processing, text classification, has become necessary in the educational domain due to the increasing number of...
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An improved term weighting method based on relevance frequency for text classification
As a vital step of text classification (TC) task, the assignment of term weight has a great influence on the performance of TC. Currently, masses of...
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MMFG: Multimodal-based Mutual Feature Gating 3D Object Detection
To address the problem that image and point cloud features are fused in a coarse fusion way and cannot achieve deep fusion, this paper proposes a...
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Best–Worst Method and Simple Additive Weighting for Selection Problems in Process Systems Engineering
The best–worst method (BWM) is a relatively new multi-criterion decision-making (MCDM) technique that was developed to overcome some of the drawbacks...
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Semiconductor Price Index Predicting Based on a Novel Improved AdaBoost Feature-Weighted Combination Model
The semiconductor price index serves as a vital metric for assessing technological developments and related market trends. Establishing a more...
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Predictive and simultaneous weighting of criteria and alternatives (PSWCA) in multi-criteria decision making based on past data
The emergence of complex technologies and economic competition in recent decades has led to the increasing importance of decisions about the future...
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Naive bayes-correlation based feature weighting technique for sports match result prediction
There has been a rapid growth in the domains of artificial intelligence, data mining and machine learning during the last few years. Machine learning...
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Machine learning based GNSS signal classification and weighting scheme design in the built environment: a comparative experiment
None-Line-of-Sight (NLOS) signals denote Global Navigation Satellite System (GNSS) signals received indirectly from satellites and could result in...
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Image retrieval using dual-weighted deep feature descriptor
Applying deep convolutional features to image retrieval has become the mainstream method in the field of image retrieval. However, the discriminative...
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Rethinking Importance Weighting for Transfer Learning
A key assumption in supervised learning is that training and test data follow the same probability distribution. However, this fundamental assumption...
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Evolutionary competitive swarm exploring optimal support vector machines and feature weighting
To deal with classification problems, support vector machines (SVMs) are utilized in a wide variety of applications as effective and powerful...
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QSFDEW: a fingerprint positioning method based on quadtree search and fractal direction entropy weighting
With the rapid development of network technology, more and more people attach importance to location-based services, which promotes the rapid...
