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AUTOMATED SYSTEM FOR DEVELOPMENT AND DEPLOYMENT OF HETEROGENEOUS PREDICTIVE MODELS

机译:异构预测模型开发和部署的自动化系统

摘要

A method and/or system for heterogeneous predictive models generation based on sampling of big data is disclosed. The method involves receiving a dataset and a target column associated with the dataset at a data processing engine from a distributed data warehouse. One or more columns associated with the dataset are classified at the data processing engine as a categorical column or a continuous column. One or more parameters in the dataset are identified to extract a sample data from the dataset. The sample data from the dataset is extracted based on the identified one or more parameters. One or more rank ordered machine learning algorithms are recommended to one or more users, to generate one or more predictive models from the sample data. One or more heterogeneous predictive models are generated based on the rank ordered algorithm through one or more iterations.
机译:公开了一种基于大数据采样的用于异构预测模型生成的方法和/或系统。该方法涉及在数据处理引擎处从分布式数据仓库接收数据集和与该数据集相关联的目标列。与数据集关联的一个或多个列在数据处理引擎中被分类为分类列或连续列。识别数据集中的一个或多个参数以从数据集中提取样本数据。基于所识别的一个或多个参数,从数据集中提取样本数据。向一个或多个用户推荐一种或多种排序的机器学习算法,以从样本数据中生成一种或多种预测模型。基于等级排序算法,通过一个或多个迭代来生成一个或多个异构预测模型。

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