Feature selection for data
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To compare the diagnostic performance of the Node-RADS scoring system and lymph node (LN) size in preoperative LN assessment for rectal cancer (RC), and to investigate whether the selection of size as the primary criterion whereas morphology as the secondary criterion for LNs can be considered the preferred method for clinical assessment.
13p vikoch 27-06-2024 1 1 Download
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This study proposes a hybrid multi-filter wrapper method for feature selection of relevant and irredundant features in software defect prediction. The proposed hybrid feature selection will be developed to take advantage of filter-filter and filter-wrapper relationships to give optimal feature subsets, reduce its evaluation cycle and subsequently improve SDP models overall predictive performance in terms of Accuracy, Precision and Recall values.
7p longtimenosee10 26-04-2024 3 1 Download
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Associative Classification is an interesting approach in data mining to create more accurate and easily interpretable predictive systems. This approach is often built on both association rule mining and classification techniques, to find a set of rules called association rules for classification (CAR) of label attributes.
7p viohoyo 25-04-2024 2 2 Download
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Ebook "Data mining - A heuristic approach" includes content: From evolution to immune to swarm to a simple introduction to modern heuristics; approximating proximity for fast and robust distance based clustering; on the use of evolutionary algorithms in data mining, the discovery of interesting nuggets using heuristic techniques, estimation of distribution algorithms for feature subset selection in large dimensionality domains,... and other contents.
310p haojiubujain09 21-11-2023 3 3 Download
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This paper introduces a high-throughput unsupervised feature selection method, which improves the robustness and scalability of electronic medical record phenotyping without compromising its accuracy.
7p visteverogers 24-06-2023 7 2 Download
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Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new methodological challenges in feature selection, choosing a distance metric that captures biological meaning, and visualization.
9p vighostrider 25-05-2023 3 2 Download
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In this paper, we propose using PCA for dimension reduction and then using decesion tree algorithms to search the space of eigenvectors with the goal of selecting a subset of eigenvectors encoding important information.
4p vifalcon 18-05-2023 7 2 Download
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The rapid growth of data has become a huge challenge for software systems. The quality of fault prediction model depends on the quality of software dataset. High-dimensional data is the major problem that affects the performance of the fault prediction models. In order to deal with dimensionality problem, feature selection is proposed by various researchers.
7p viplato 05-04-2022 17 1 Download
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Cell type identification is one of the most important questions in single-cell RNA sequencing (scRNA-seq) data analysis. With the accumulation of public scRNA-seq data, supervised cell type identification methods have gained increasing popularity due to better accuracy, robustness, and computational performance.
23p viarchimedes 26-01-2022 9 0 Download
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Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple sources, including biological variation in cellular state as well as technical variation introduced during experimental processing.
20p viarchimedes 26-01-2022 6 0 Download
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Maintaining landscape connectivity through identifying movement corridors is the most recommended conservation strategy to reduce the negative impacts of habitat loss and isolation. The basis of most connectivity modelling approaches for modelling corridors is that species choose movement pathways based on the same criteria they used to choose habitats. However, species behave differently in using landscape elements for moving than for selecting habitat. In other words, suitability of a given landscape feature may differ between moving and habitat use stages.
12p dolomite36 30-12-2021 14 0 Download
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This research proposes a framework for signal processing and information fusion of spatialtemporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment.
16p guernsey 28-12-2021 10 0 Download
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The novelty of our approach relies on a proper flow and fusion of information (DGHNL structure and its optimization). We show that the proposed DGHNL model with a 29-layer structure is capable to achieve the prediction accuracy of 94.60% (54 errors per 1000 classifications) for the Statlog German credit approval data.
18p guernsey 28-12-2021 8 1 Download
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The specific objectives were: 1) to improve the ensemble classifier through data-level approach (sampling and feature selection); 2) to perform experiments on sampling, feature selection, and ensemble classifier model; and 3) to evaluate the performance of the ensemble classifier.
31p spiritedaway36 28-11-2021 16 4 Download
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This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. Based on the feature selection results, the Optimized BPNN outperformed other methods for all datasets.
27p spiritedaway36 28-11-2021 14 2 Download
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This paper proposes a cluster based PSO feature construction approach called ClusPSOFC. The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC.
34p spiritedaway36 28-11-2021 6 1 Download
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Miniature size in horses represents an extreme reduction of withers height that originated after domestication. In some breeds, it is a highly desired trait representing a breed- or subtype-specific feature. The genomic changes that emerged due to strong-targeted selection towards this distinct type remain unclear.
15p vibeauty 23-10-2021 9 1 Download
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Antimicrobial peptides are a promising alternative for combating pathogens resistant to conventional antibiotics. Computer-assisted peptide discovery strategies are necessary to automatically assess a significant amount of data by generating models that efficiently classify what an antimicrobial peptide is, before its evaluation in the wet lab.
14p vitzuyu2711 29-09-2021 15 1 Download
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The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far from being satisfactory due to their limitation in using unsupervised learning methods.
17p vijeeni2711 30-06-2021 12 1 Download
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The present paper concerns the semantic features of modality markers in Linguistics research papers across two subsets, the indexed journals and the non-indexed English-medium journals published in Vietnam. The data is 30 Linguistics research papers from 2017 to 2019, selected from English for Specific Purposes and VNU Journal of Foreign Studies
10p nguaconbaynhay12 09-06-2021 14 3 Download