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Evaluating and Improving Linear Regression Based Profiling: On the Selection of Its Regularization.

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Title: Evaluating and Improving Linear Regression Based Profiling: On the Selection of Its Regularization.
Authors: Lu, Xiang-Jun1, Zhang, Chi1, Gu, Da-Wu1, dwgu@sjtu.edu.cn, Liu, Jun-Rong1,2, Peng, Qian3, Zhang, Hai-Feng1,4
Source: Journal of Computer Science & Technology (10009000); Oct2020, Vol. 35 Issue 5, p1175-1197, 23p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 146711059
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Evaluating and Improving Linear Regression Based Profiling: On the Selection of Its Regularization.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=146711059
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      – Type: doi
        Value: 10.1007/s11390-020-9669-0
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      – Code: eng
        Text: English
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        PageCount: 23
        StartPage: 1175
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      – TitleFull: Evaluating and Improving Linear Regression Based Profiling: On the Selection of Its Regularization.
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            NameFull: Lu, Xiang-Jun
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            NameFull: Zhang, Chi
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            NameFull: Gu, Da-Wu
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            NameFull: Liu, Jun-Rong
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            NameFull: Peng, Qian
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            – D: 01
              M: 10
              Text: Oct2020
              Type: published
              Y: 2020
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