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Support Vector Machine Classification and Regression Prioritize Different Structural Features for Binary Compound Activity and Potency Value Prediction
[Image: see text] In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among the most widely used machine learning methods for the identification of new active compounds. In addition, support vector regression (SVR) has become a preferred approach for modeli...
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| הוצא לאור ב: | ACS Omega |
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| Main Authors: | , , |
| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
American Chemical Society
2017
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| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6045367/ https://ncbi.nlm.nih.gov/pubmed/30023518 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acsomega.7b01079 |
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