The train and test kernel matrix matrices. by Aninda Astuti (21736334)

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The results of 10 performance metrics from the miRNA biomarker study (M0 vs M1), comparing NQE+SVC and NQE+QSVC in the 6 PCs case. by Aninda Astuti (21736334)

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The results of the ten performance metrics for NQE+SVC vs NQE+QSVC based on classifying miRNA expression profiles. by Aninda Astuti (21736334)

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Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this an... by Aninda Astuti (21736334)

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Binary Classification Evaluation showing the mean F1 scores (rounded to 3 decimal places) for the Multiple Category approach for the Unseen Testing Categories. by David Kilroy (10661225)

An example binary tree for H-SuperVec(X): A hierarchical structure obtained by partitioning the class labels of each parent node into equal size subsets. by Dhananjay Kimothi (8575089)

The maximum accuracy (lowest error rate) with the least number of ANOVA-ranked genes achieved by different feature filtering methods and classification algorithms refined by SIRRFE under various classification tasks, including: the multiclass classification for distinguishing each individual PAH patient group (Control <i>vs</i>.... by Song Cui (553627)

“…<p>The maximum accuracy (lowest error rate) with the least number of ANOVA-ranked genes achieved by different feature filtering methods and classification algorithms refined by SIRRFE under various classification tasks, including: the multiclass classification for distinguishing each individual PAH patient group (Control <i>vs</i>. …”

Binary Classification Evaluation showing the mean F1 scores (rounded to 3 decimal places) for the One Category and Multiple Category approaches across the Seen Testing Categories. by David Kilroy (10661225)

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

P-value (rounded to 3 decimal places) for the Mann-Whitney U test of F1 scores from the One Category approach vs the best baseline approach for Binary Classification Evaluation. by David Kilroy (10661225)

Ordinal regression task performance. by Thierry Jean (20691795)

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P-value for the Mann-Whitney U Rank Test of F1 scores (rounded to 3 decimal places) from One Category approach vs Multiple Category approach for Binary Classification Evaluation ac... by David Kilroy (10661225)

Flowchart for classification tasks in automated extinction risk assessment method, using the XGBoost algorithm [29]. by Gabriel Henrique de Oliveira Caetano (12647413)

Characteristics of the data sets used to evaluate Machine Learning and Deep Learning models for arboviral diseases classification. by Sebastião Rogério da Silva Neto (11944944)

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Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx by Lu Huang (211625)

“…The subject was classified as either Success or Unsuccess group according to whether they had completed the on-road test. A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.…”

Summary of all non-clinical data (laboratory and others) presented in the data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

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Models used in the works divided by the main problems. by Sebastião Rogério da Silva Neto (11944944)

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Study selection. by Sebastião Rogério da Silva Neto (11944944)

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