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Random forest classification is a well known machine learning technique that generates classifiers in the form of an ensemble ("forest") of decision trees. The classification of an input sample is determined by the majority classification by the ensemble. Traditional random forest classifiers can be highly effective, but classification using a random forest(More)
The Hybrid Memory Cube is an early commercial product embodying attributes of future stacked DRAM architectures, namely large capacity, high bandwidth, on-package memory controller, and high speed serial interface. We study the performance and energy of a Gen2 HMC on data-centric workloads through a combination of emulation and execution on an HMC FPGA(More)
Formulation changes at later stages of biotherapeutics development require biocomparability (BC) assessment. Using simulation, this study aims to determine the potential effect of bias difference observed between the two formulations after spiking into serum in passing or failing of a critical BC study. An ELISA method with 20% total error was used to(More)
Manufacturing changes during a biological drug product life cycle occur often; one common change is that of the manufacturing site. Comparability studies may be required to ensure that the changes will not affect the pharmacokinetic properties of the drug. In addition, the bioanalytical method for sample analysis may evolve during the course of drug(More)
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