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首页> 外国专利> AMD-Data Analysis:ACADEMY DATA ANALYSIS USING MACHINE LEARNING, DEEP LEARNING PROGRAMMING

AMD-Data Analysis:ACADEMY DATA ANALYSIS USING MACHINE LEARNING, DEEP LEARNING PROGRAMMING

机译：AMD数据分析：使用机器学习，深度学习编程进行学院数据分析

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#$%^&*AU2020102379A420201105.pdf#####ABSTRACT Our Invention "AMD-Data Analysis"is an embodiments are directed towards classifying data using machine learning, deep learning that may be incrementally refined based on expert input. The invented technology is also the provided to a deep learning model that may be trained based on a classifiers and sets of mapping, training data and testing data. If the number of classification errors exceeds a defined fixed table data and threshold classifier may be modified based on data corresponding to observed classification errors. The invented technology a three type of learning model (fast, medium, slower) may be trained based on the modified classifiers the data and the data corresponding to the observed classification errors and another confidence value may be generated and associated with the classification of the data by the all type of learning, mapping model. The invented technology re-information may be generated based on a comparison result of the confidence value associated with the all learning model and the confidence value associated with the machine, deep learning model. The invention alos provides methods of analyzing or displaying data. The invention provides methods for visualizing or displaying high dynamic range data obtained from flow cytometry analyses. Related systems and computer programs products are also provided. 28NO DvT YE02 ASSOCZATE HISTCRICAL NETWORK iPORMATION W"TI ENT=T BASED ON 90 CLASS OF DETT BUFFR REAL-EA NEaWOK -- 906 INFORM0ATIONV FOR ENTITY rCL ASSIFY NETWORK ACTI-V=T 908r USING MOD)E L ADD ANOMALIAES NE W ENTITY TO NUE FO 1 NO FIG. 5: SHOWS A FLOWCHART FOR A PROCESS FOR REACTING TO THE DISCOVERY OF NEW ENTITIES IN IN A MONITORED NETWORK IN ACCORDANCE WITH AT LEAST ONE OF THE VARIOUS EMBODIMENTS;1000 1002 FIG 6 ISA ABL DAGRMHOWNGTHESAPreSULtSeFd CONFsIO ARXFRATS FASSE DESIGNED~~ Cas TOCASFAOUET NOOEO HE ClassE IN ACORDANCEWTATLSTOEFTH CVARIOU EMBODIMENTS;
机译：＃$％^＆* AU2020102379A420201105.pdf #####抽象我们的发明“ AMD-数据分析”是针对的一个实施例。使用机器学习对数据进行分类，深度学习可能会逐步进行根据专家的意见进行完善。本发明的技术也被提供给可以基于分类器和一组集合进行训练的深度学习模型制图，训练数据和测试数据。如果数量分类错误超过定义的固定表数据，并且阈值分类器可以基于对应于观察到的分类错误的数据。发明技术三种类型的学习模型（快速，中等，较慢）可以根据修改后的分类器将数据与观察到的数据相对应可能会产生分类错误和另一个置信度值，并且通过所有类型的学习，映射与数据分类相关联模型。本发明的技术重新信息可以基于与所有学习模型相关的置信度值的比较结果以及与机器，深度学习模型相关的置信度值。的本发明还提供了分析或显示数据的方法。本发明提供可视化或显示获得的高动态范围数据的方法从流式细胞仪分析。相关系统和计算机程序产品还提供。28没有DvTYE02关联历史网络iPORMATION W“ TI ENT = T基于90等级BUFFR REAL-EA NEAWOK-906实体信息rCL验证网络ACTI-V = T 908r使用MOD）添加肛门新佛像1没有图。 5：显示受监控的新实体发现过程的流程图至少有一个实施例中的网络10001002图6 ISA ABL DAGRMHOWNGTHESAPreSultSeFd CONFsIO ARXFRATS FASSE设计~~ CAS TOCASFAOUET NOOEO HE ClassE在ACORDANCEWTATLSTOEFTHCVARIOU实施例;

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