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METHODS AND APPARATUS FOR CONDITIONAL CLASSIFIER CHAINING IN A CONSTRAINED MACHINE LEARNING ENVIRONMENT
METHODS AND APPARATUS FOR CONDITIONAL CLASSIFIER CHAINING IN A CONSTRAINED MACHINE LEARNING ENVIRONMENT
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机译:受限机器学习环境中条件分类器链的方法和装置
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摘要
Methods, apparatus, systems, and articles of manufacture for conditional classifier chaining in a constrained machine learning environment are disclosed. An example apparatus includes a classification controller to select a first model to be utilized to classify a first feature identified from sensor data. A memory controller is to copy the first model to a memory. A machine learning processor is to apply the first model to the first feature to create a first classification output, the first classification output indicating an identified class. The classification controller is to, in response to a determination that the first classification output identifies a second model to be used for classification, instruct the memory controller to load the second model into the memory. The machine learning processor is to apply the second model to the second feature to create a second classification output.
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