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Using Random Forest To Model the Domain Applicability of Another Random Forest Model

https://doi.org/10.1021/ci400482e
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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The One‐Class Classification Approach to Data Description and to Models Applicability Domain
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Target‐Driven Subspace Mapping Methods and Their Applicability Domain Estimation
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Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules
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Inflation of correlation in the pursuit of drug-likeness
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QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality
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The National Center for Biotechnology Information
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Can we estimate the accuracy of ADME–Tox predictions?
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The importance of the domain of applicability in QSAR modeling
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Fingerprint-based clustering applied to define a QSAR model use radius
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Atom pairs as molecular features in structure-activity studies: definition and applications
inferredcites →https://doi.org/10.1021/ci034160gopenalex-snapshot
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
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Determining the Validity of a QSAR Model − A Classification Approach
inferredcites →https://doi.org/10.1021/ci049782wopenalex-snapshot
Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR
inferredcites →https://doi.org/10.1021/ci0500379openalex-snapshot
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling
inferredcites →https://doi.org/10.1021/ci0500381openalex-snapshot
A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models
inferredcites →https://doi.org/10.1021/ci1000967openalex-snapshot
Assessment of Methods To Define the Applicability Domain of Structural Alert Models
inferredcites →https://doi.org/10.1021/ci100253ropenalex-snapshot
Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set
inferredcites →https://doi.org/10.1021/ci200311wopenalex-snapshot
Predictive Models for Cytochrome P450 Isozymes Based on Quantitative High Throughput Screening Data
inferredcites →https://doi.org/10.1021/ci300004nopenalex-snapshot
Three Useful Dimensions for Domain Applicability in QSAR Models Using Random Forest
inferredcites →https://doi.org/10.1021/ci300554topenalex-snapshot
Interpretable, Probability-Based Confidence Metric for Continuous Quantitative Structure–Activity Relationship Models
inferredcites →https://doi.org/10.1021/ci400001uopenalex-snapshot
Quantitative Structure–Activity Relationship Models of Clinical Pharmacokinetics: Clearance and Volume of Distribution
inferredcites →https://doi.org/10.1021/ci400084kopenalex-snapshot
Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.
inferredcites →https://doi.org/10.1021/ci600332jopenalex-snapshot
Contemporary QSAR Classifiers Compared
inferredcites →https://doi.org/10.1021/ci800151mopenalex-snapshot
Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection
inferredcites →https://doi.org/10.1021/ci9000579openalex-snapshot
Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models
inferredcites →https://doi.org/10.1021/ci900313uopenalex-snapshot
Chemical Domain of QSAR Models from Atom-Centered Fragments
inferredcites →https://doi.org/10.1021/ci950274jopenalex-snapshot
Chemical Similarity Using Physiochemical Property Descriptors
inferredcites →https://doi.org/10.1021/ci990131nopenalex-snapshot
QM/NN QSPR Models with Error Estimation: Vapor Pressure and LogP
inferredcites →https://doi.org/10.1186/1758-2946-1-11openalex-snapshot
DPRESS: Localizing estimates of predictive uncertainty
inferredcites →https://doi.org/10.1371/journal.pone.0048723openalex-snapshot
No Longer Confidential: Estimating the Confidence of Individual Regression Predictions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Additional file 1 of QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction
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Additional file 2 of Profiling and analysis of chemical compounds using pointwise mutual information
inferred← citeshttps://doi.org/10.6084/m9.figshare.16650122openalex-snapshot
Additional file 1 of A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling
inferred← citeshttps://doi.org/10.6084/m9.figshare.17982809openalex-snapshot
Additional file 1 of HobPre: accurate prediction of human oral bioavailability for small molecules
inferred← citeshttps://doi.org/10.70675/00fff70azab21z46edz8364z60031c95c00fopenalex-snapshot
Applications of proteochemometrics (PCM) : from species extrapolation to cell-line sensitivity modelling
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