Predicting a biological response of molecules from their chemical properties using diverse and optimized ensembles of stochastic gradient boosting machine
Abstract:The development of a new drug largely depends on trial and error. It typically involves synthesizing thousands of compounds that finally becomes a drug. This process is extremely expensive and slow. Therefore, the ability to accurately predict the biological activity of molecules, and understand the rationale behind those predictions would be of great value to the pharmaceutical industry. Gradient Boosting Machines (GBMs) are powerful ensemble learning techniques that have been successfully applied to several … Show more
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