rf learner (KNIME GmbH)

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KNIME GmbH rf learner
Rf Learner, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/rf+learner/rf+learner+node/pmc11783816-330-2-1
Average 90 stars, based on 1 article reviews

rf learner - by Bioz Stars, 2026-09

90/100 stars

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Article Title: Development and experimental validation of a machine learning model for the prediction of new antimalarials.
Article Snippet: In KNIME ‘RF Learner’ node, the mtry value is fixed to the square root of p which is shown to perform well [35].

Article Title: Discovery of New STAT3 Inhibitors as Anticancer Agents Using Docking-Based Ligand- Receptor Contacts Fingerprints and Bioactivity - Classifying Machine Learning
Article Snippet: We implemented RF Learner node within KNIME Analytics Platform (Version 4.3.3) with the following settings: Splitting criterion is Information Gain Ratio (which normalizes the standard information gain by the split entropy to overcome any unfair preference for nominal splits with many child nodes)., Number of trees = 100.

Article Title: Discovery of new potent lysine specific histone demythelase-1 inhibitors (LSD-1) using structure based and ligand based molecular modelling and machine learning
Article Snippet: The RF learner node within KNIME Analytics Platform (Version 4.3.2) was implemented with the following parameters: Tree options: no minimum node size or maximum tree depth were specified, Split method: GINI, Number of trees = 100.

Article Title: Docking-generated multiple ligand poses for bootstrapping bioactivity classifying Machine Learning: Repurposing covalent inhibitors for COVID-19-related TMPRSS2 as case study
Article Snippet: We implemented RF learner node within KNIME Analytics Platform (Version 4.1.3) with the following settings: Splitting criterion is the Information Gain Ratio (which normalizes the standard information gain by the split entropy to overcome any unfair preference for nominal splits with many child nodes), Number of trees = 100.

Article Title: Development and experimental validation of a machine learning model for the prediction of new antimalarials.
Article Snippet: Next, we used the ‘RF Learner’ and ‘RF Prediction’ nodes available in KNIME to build a predictive model.

Article Title: Development and experimental validation of a machine learning model for the prediction of new antimalarials
Article Snippet: In KNIME ‘RF Learner’ node, the m try value is fixed to the square root of p which is shown to perform well [ ].

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Article Title: PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach.
Article Snippet: .. Replacing the RF classifier in the implementation of PriPath can be done by the users via replacing the RF node with, for example, the support vector machine node in KNIME. ..

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