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Journal of Statistical Software
Research Hotspot & Journal Scope - Selection


Journal of Statistical Software - DOI: 10.18637/jss.v091.i09
Fuzzy Forests: Extending Random Forest Feature Selection for Correlated, High-Dimensional Data

Daniel Conn · Tuck C. Ngun · Gang Li · Christina M. Ramirez ·

Computer Science
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Journal of Statistical Software - DOI: 10.18637/JSS.V088.I09
BTLLasso: A Common Framework and Software Package for the Inclusion and Selection of Covariates in Bradley-Terry Models

Gunther Schauberger · Gerhard Tutz ·

Computer Science
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Purpose Use of the United States Medical Licensing Examination (USMLE) for residency selection has been criticized for its inability to predict clinical performance and potential bias against underrepresented minorities (URMs).

Can Better Selection Tools Help Us Achieve Our Diversity Goals in Postgraduate Medical Education? Comparing Use of USMLE Step 1 Scores and Situational Judgment Tests at 7 Surgical Residencies [10.1097/ACM.0000000000003092]


The purpose of this study was to analyze the influence of merit selection criteria on private sector participation in provision of quality education in Elgeyo-Marakwet County.

Influence of Merit Selection Criteria on Private Sector Participation in Provision of Quality Education in Elgeyo-Marakwet County [10.6007/ijarbss/v9-i6/5928]


We conclude that the quoted maximum heat treatment temperature alone is not sufficient to specify the properties of GC and that a careful microstructural examination of the material should be used to inform materials selection.

The composition, structure and properties of four different glassy carbons [10.1016/J.JNONCRYSOL.2019.119561]


The reason is partly that driver and sensor node selection problems for nonlinear complex networks have not been studied systematically, which differs greatly from the relatively comprehensive mathematical development for the linear counterpart.

Structural Accessibility and Its Applications to Complex Networks Governed by Nonlinear Balance Equations [10.1109/TAC.2019.2901822]


The modelling step is input preparation, Artificial Neural Network (ANN) structure determination, optimizer and loss function selection, training ANN and model evaluation.

Modeling Vertical Roller Mill Raw Meal Residue by Implementing Neural Network [10.1109/ICIRD47319.2019.9074747]


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