Great machine learning performance with multiple classification algorithms. by Sydney C. Weiser (15383531)

Random forest algorithm: Method and example results. by Natalie Weed (7345124)

“…(<b>D</b>) Schematic illustration of arrays input into Random Forest algorithm. Columns correspond to gene, rows to pixels in the top projection data set. …”

Clustering evaluation results of the FCM algorithm. by Xini Fang (20861990)

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The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

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Data_Sheet_1_Using random forest algorithm for glomerular and tubular injury diagnosis.docx by Wenzhu Song (12532351)

San Diego PIRC (Primary Infection Resource Consortium) data: 1998-2019. by Sepideh Mazrouee (5191339)

Single cell RNA-sequencing expression plot. by Natalie Weed (7345124)

DataSheet_1_cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine.pdf by Jiaxin Long (16620456)

“…We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. …”

Accession list and passport data. by Diego Felipe Conejo-Rodríguez (18495740)

“…Descriptors discriminating most accessions were identified using a random forest algorithm. The most-valuable classification descriptors for peanuts were 100-seed weight and days to flowering, and for beans, days to flowering and primary seed color. …”

The robustness test results of the model. by Xini Fang (20861990)

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The relevant code in the manuscript can be found in the supporting information data file. by Xini Fang (20861990)

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Model performance comparison under different parameter settings. by Xini Fang (20861990)

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CRITIC weight calculation results for corporate operational risk warning indicators. by Xini Fang (20861990)

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Feature importance ranking results of model risk indicators. by Xini Fang (20861990)

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The membership distribution of various indicators in different risk categories by the FCM algorithm (Note: Clustering categories (Medium risk (2, 3)/ High risk (5)/ Risk-free (1)/... by Xini Fang (20861990)

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Risk prediction results of the RF model improved by FCM clustering ((a) Different risk prediction results; (b) Prediction results of different models). by Xini Fang (20861990)

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Parameter optimization results of the RF model improved by FCM clustering. by Xini Fang (20861990)

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Corporate operational risk indicator statistical differences results. by Xini Fang (20861990)

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Construction process of RF. by Xini Fang (20861990)

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