Abstract
The proposed system is capable to build an intelligent service using cloud data with the following features: The collaborative cloud data sets can be integrated from various ocular sources and standardized to have a uniformity; The integrated standard data set is then processed and transformed to generate features for machine learning models automatically; The predictive machine learning models can be trained with the stratified random sampled data and ranked features from the transformed datasets.
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R.K. Ando, T. Zhang, A framework for learning predictive structures from multiple tasks and unlabeled data. J. Mach. Learn. Res. (JMLR) 6, 1817–1953, p. 14 (2005)
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Banerjee, A., SreeYella, K., Mustafi, J. (2021). Automatic Standardization of Data Based on Machine Learning and Natural Language Processing. In: Sharma, N., Chakrabarti, A., Balas, V.E., Martinovic, J. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 1175. Springer, Singapore. https://doi.org/10.1007/978-981-15-5619-7_4
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DOI: https://doi.org/10.1007/978-981-15-5619-7_4
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