Results 11 to 20 of about 248,320 (248)
Improving Machine Learning Performance by Eliminating the Influence of Unclean Data [PDF]
Engineering and Technology Journal, 2022 Regardless of the data source and type (text, digital, photo group, etc.), they are usually unclean data. The term (unclean) means that data contains some bugs and paradoxes that can strongly impact machine learning processes.
Murtadha Ressan, Rehab Hassan
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Data pre-processing for analyzing microbiome data – A mini review
Computational and Structural Biotechnology Journal, 2023 The human microbiome is an emerging research frontier due to its profound impacts on health. High-throughput microbiome sequencing enables studying microbial communities but suffers from analytical challenges.
Ruwen Zhou +4 more
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A Memory-Efficient Encoding Method for Processing Mixed-Type Data on Machine Learning
Entropy, 2020 The most common machine-learning methods solve supervised and unsupervised problems based on datasets where the problem’s features belong to a numerical space.
Ivan Lopez-Arevalo +5 more
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Missing value imputation Techniques: A Survey
UHD Journal of Science and Technology, 2023 Numerous of information is being accumulated and placed away every day. Big quantity of misplaced areas in a dataset might be a large problem confronted through analysts due to the fact it could cause numerous issues in quantitative investigates.
Wafaa Mustafa Hameed, Nzar A. Ali
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Data Reduction Techniques: A Comparative Study
Journal of Kufa for Mathematics and Computer, 2022 Data preprocessing in general and data reduction in specific represent the main steps in data mining techniques and algorithms since data in real world due to its vastness, the analysis will take a long time to complete .Almost all mining techniques ...
Ahmed AlKarawi, Kadhim AlJanabi
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Pre-processing Agilent microarray data
BMC Bioinformatics, 2007 Background Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression
Schaeffer Edward +7 more
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protGear: A protein microarray data pre-processing suite
Computational and Structural Biotechnology Journal, 2021 Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data.
Kennedy Mwai +12 more
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Auto-Prep: Efficient and Automated Data Preprocessing Pipeline
IEEE Access, 2022 Data preprocessing is crucial in the Machine Learning pipeline because the models’ learning ability directly affects the quality of data and the underlying information acquired from this stage.
Mehwish Bilal +5 more
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Data Preprocessing Technology in Chemical Process Data Mining
Chemical Engineering Transactions, 2017 This paper studies the data preprocessing technology in chemical process data mining. It mainly studies the real-time chemical process data in-depth from the perspective of software development and explores various kinds of real-time data preprocessing ...
Feifei Yang
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Preprocessing differential methylation hybridization microarray data
BioData Mining, 2011 Background DNA methylation plays a very important role in the silencing of tumor suppressor genes in various tumor types. In order to gain a genome-wide understanding of how changes in methylation affect tumor growth, the differential methylation ...
Sun Shuying +4 more
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