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Machine learning based quantification of performance impact of data veracity
Machine learning based quantification of performance impact of data veracity
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机译：基于机器学习的数据绩效影响的量化
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摘要
In some examples, machine learning based quantification of performance impact of data irregularities may include generating an irregularity feature vector for each text analytics application of a plurality of text analytics applications. Normalized data associated with a corresponding text analytics application may be generated for each text analytics application and based on minimization of irregularities present in un-normalized data associated with the corresponding text analytics application. An un-normalized data machine learning model may be generated for each text analytics application and based on the un-normalized data associated with the corresponding text analytics application. A normalized data machine learning model may be generated for each text analytics application and based on the normalized data associated with the corresponding text analytics application. A difference in performances may be determined with respect to the un-normalized data machine learning model and the normalized data machine learning model.
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