Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling-Reference-Cited by-同舟云学术

Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling

Published:2003-11-01 Issue:6 Volume:43 Page:1947-1958
ISSN:0095-2338
Container-title:Journal of Chemical Information and Computer Sciences
language:en
Short-container-title:J. Chem. Inf. Comput. Sci.

Author:

Svetnik Vladimir¹,Liaw Andy¹,Tong Christopher¹,Culberson J. Christopher¹,Sheridan Robert P.¹,Feuston Bradley P.¹

Affiliation:

1. Biometrics Research, Merck Research Laboratories, P.O. Box 2000, Rahway, New Jersey 07065, Molecular Systems, Merck Research Laboratories, P.O. Box 4, West Point, Pennsylvania 19486, and Molecular Systems, Merck Research Laboratories, P.O. Box 2000, Rahway, New Jersey 07065

Publisher

American Chemical Society (ACS)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci034160g

Reference39 articles.

1. Analysis of a Large Structure/Biological Activity Data Set Using Recursive Partitioning

2. Predicting CNS Permeability of Drug Molecules: Comparison of Neural Network and Support Vector Machine Algorithms

3. Extending the trend vector: The trend matrix and sample-based partial least squares

4. Classification of Multidrug-Resistance Reversal Agents Using Structure-Based Descriptors and Linear Discriminant Analysis

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