Results 201 to 210 of about 819,529 (261)

Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. [PDF]

Comput Med Imaging Graph
Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S.   +5 more
europepmc   +1 more source

Evolution‐guided yeast complementation reveals functional differences in human PSPH variants

FEBS Open Bio, EarlyView.
Ancient genomes can help guide which human genetic variants are tested experimentally. This study applies that idea to PSPH, a gene involved in serine biosynthesis, and uses high‐throughput yeast complementation to compare variant function. The findings reveal measurable differences among selected alleles and illustrate the value of evolution‐guided ...
Mauricio Campa‐Álvarez, Diana Ascencio, Miguel Vallebueno‐Estrada, Eduardo González‐Orozco, Christian Eduardo Martínez‐Guerrero, Rafael Montiel, Alexander DeLuna   +6 more
wiley   +1 more source

Classification performance bias between training and test sets in a limited mammography dataset. [PDF]

PLoS One
Hou R, Lo JY, Marks JR, Hwang ES, Grimm LJ.   +4 more
europepmc   +1 more source

TopoGeoFusion: Integrating object topology based feature computation methods into geometrical feature analysis to enhance classification performance. [PDF]

MethodsX
Rani NS, Sai KS, Pushpa BR, Krishna AS, Sangamesha MA, Bhavya KR, Devadas RM, Hiremani V.   +7 more
europepmc   +1 more source

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning. [PDF]

Molecules
Zhang P, Xu J, Du B, Yang Q, Liu B, Xu J, Tong Z.   +6 more
europepmc   +1 more source

Comparing human text classification performance and explainability with large language and machine learning models using eye-tracking. [PDF]

Sci Rep
Divya Venkatesh J, Jaiswal A, Nanda G.
europepmc   +1 more source

Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines. [PDF]

Sci Data
Valencia EM, Maki KA, Dootz JN, Barb JJ.
europepmc   +1 more source

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A classification performance measure considering the degree of classification difficulty

Neurocomputing, 2016
In the field of classification, classification difficulty of instances is one of vital factors that influence the performance of classifiers, however it has been totally neglected. In this paper, a new performance measure for classification algorithms based on Receiver Operator Characteristic (ROC) curves is proposed with the ability of incorporating ...
Xiaoli Zhang, Xiongfei Li
exaly   +2 more sources

An experimental comparison of performance measures for classification

Pattern Recognition Letters, 2009
Performance metrics in classification are fundamental in assessing the quality of learning methods and learned models. However, many different measures have been defined in the literature with the aim of making better choices in general or for a specific application area. Choices made by one metric are claimed to be different from choices made by other
JOSÉ Hernández-Orallo, Cesar Ferri Ramirez   +1 more
exaly   +2 more sources