Results 71 to 80 of about 2,965,444 (278)
Get another label? improving data quality and data mining using multiple, noisy labelers [PDF]
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, 2008 This paper addresses the repeated acquisition of labels for data items when the labeling is imperfect. We examine the improvement (or lack thereof) in data quality via repeated labeling, and focus especially on the improvement of training labels for supervised induction.
Victor S. Sheng +2 more
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FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
Active Learning for Uneven Noisy Labeled Data in Mention-Level Relation Extraction
IEEE Access, 2019 Mention-level relation extraction (mRE) plays an important role in extracting relational information from short texts such as those exchanged in a social network.
Wei Yuliang +3 more
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Synthetic Oversampling of Multi-label Data Based on Local Label Distribution [PDF]
, 2020 Class-imbalance is an inherent characteristic of multi-label data which affects the prediction accuracy of most multi-label learning methods. One efficient strategy to deal with this problem is to employ resampling techniques before training the classifier.
Liu, Bin, Tsoumakas, Grigorios
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Cell wall target fragment discovery using a low‐cost, minimal fragment library
FEBS Letters, EarlyView.LoCoFrag100 is a fragment library made up of 100 different compounds. Similarity between the fragments is minimized and 10 different fragments are mixed into a single cocktail, which is soaked to protein crystals. These crystals are analysed by X‐ray crystallography, revealing the binding modes of the bound fragment ligands.
Kaizhou Yan +5 more
wiley +1 more source
FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
Feature Selection for Partially Labeled Data Based on Neighborhood Granulation Measures
IEEE Access, 2019 As an effective feature selection technique, rough set theory plays an important part in machine learning. However, it is only applicable to labeled data.
Bingyang Li, Jianmei Xiao, Xihuai Wang
doaj +1 more source
Strength of Relationship Between Multi-labeled Data and Labels [PDF]
, 2015 Collected data must be organized properly to utilize well and classification of data is one of the efficient methods. Individual data or an object is classified to categories and annotated with labels of those categories. Giving ranks to labels of objects in order to express how close objects are to the categories enables us to use objects more ...
Kuzunishi, Masahiro, Furukawa, Tetsuya
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FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
wiley +1 more source
Displaying Labeled Quantitative Data
Social Communication, 2019 The information world is full of labeled quantitative data, in which a number of qualitative cat-egories are to be compared based on a quantitative variable. Their graphical representations arevarious and serve different audiences and purposes. Based on a simple data set and its different vi-sualizations, we will play with the data and their visual ...
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