13 papers · ranked by Valyu relevance
Reiner Jedermann, Walter Lang, Leopoldo Angrisani, Domenico Accardo
Analog sensors often require complex mathematical models for data analysis. Digital twins (DTs) provide platforms to display sensor data in real time but still lack generic solutions regarding how mathematical models and algorithms can be integrated. Based on previous tests for monitoring and predicting banana fruit…
Yanxiong Peng, Wenyuan Li, Ying Liu
Microarrays allow researchers to monitor the gene expression patterns for tens of thousands of genes across a wide range of cellular responses, phenotype and conditions. Selecting a small subset of discriminate genes from thousands of genes is important for accurate classification of diseases and phenotypes. Many…
Fujun Wang, Xing Wang, Seyedali Mirjalili
Feature selection is an important task in big data analysis and information retrieval processing. It reduces the number of features by removing noise, extraneous data. In this paper, one feature subset selection algorithm based on damping oscillation theory and support vector machine classifier is proposed. This…
Rahi Jain, Wei Xu
Background Feature selection is important in high dimensional data analysis. The wrapper approach is one of the ways to perform feature selection, but it is computationally intensive as it builds and evaluates models of multiple subsets of features. The existing wrapper algorithm primarily focuses on shortening the…
Hsueh-Wei Chang, Yu-Hsien Chiu, Hao-Yun Kao, Cheng-Hong Yang + 1 more
'Wen-Hsien Ho'] An essential task in a genomic analysis of a human disease is limiting the number of strongly associated genes when studying susceptibility to the disease. The goal of this study was to compare computational tools with and without feature selection for predicting osteoporosis outcome in Taiwanese women…
Grace Yee Lin Ng, Shing Chiang Tan, Chia Sui Ong, Guanghui Liu
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell…
Yongtao Shi, Yuefeng Zheng, Xiaotong Bai, Elnaz Pashaei
Recently, hybrid feature selection methods have demonstrated excellent performance on high-dimensional data, but many of these methods tend to yield relatively homogeneous feature subsets. To address this, we propose a novel hybrid feature selection algorithm called the Hybrid Multiple Filter-Wrapper algorithm. This…
Firuz Kamalov, Hana Sulieman, Sherif Moussa, Jorge Avante Reyes + 1 more
'Murodbek Safaraliev'] It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. To address this issue, we propose a highly effective approach, called Nested Ensemble…
Abdullateef O. Balogun, Shuib Basri, Saipunidzam Mahamad, Luiz Fernando Capretz + 4 more
The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types…
Othman Soufan, Dimitrios Kleftogiannis, Panos Kalnis, Vladimir B. Bajic + 1 more
'Vladimir B. Bajic' 'Dinesh Gupta'] Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification…
Divo Dharma Silalahi, Habshah Midi, Jayanthi Arasan, Mohd Shafie Mustafa + 1 more
'Mohd Shafie Mustafa' 'Jean-Pierre Caliman'] The extraction of relevant wavelengths from a large dataset of Near Infrared Spectroscopy (NIRS) is a significant challenge in vibrational spectroscopy research. Nonetheless, this process allows the improvement in the chemical interpretability by emphasizing the chemical…
Linzhong Li, RobertM Seymour, Stephen Baigent
Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method…
Rob Smith, Ryan Williamson, Dan Ventura, John T Prince
Background The number and diversity of wrappers for chemoinformatic toolkits suggests the diverse needs of the chemoinformatic community. While existing chemoinformatics libraries provide a broad range of utilities, many chemoinformaticians find compiled language libraries intimidating, time-consuming, arcane, and…