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• W4317242512 abstract "Machine Learning is a basic innovation in foreseeing results in view of data. Four famous Big Data machine learning algorithms are tended to in this paper: Bayesian Decision Theory Classification, and Linear Regression. The underlying two are overseen learning algorithms, the third an independent learning algorithm, and the fourth a relationship algorithm. Advantages of machine learning integrate flexibility and adaptability differentiated and customary biostatistical methods, which makes it deployable for certain tasks, similar to bet partition, finding and gathering, and perseverance assumptions. One more benefit of machine learning algorithms is the capacity to examine assorted data types. Every methodology is broadly explored and examined. Likewise, the accentuation is placed on how the four techniques transaction with one another to rouse investigation of more strong and data-proficient algorithms. At long last, the review portrays the impediments, talks about research difficulties, and recommends future chances to propel the examination on data-proficiency in machine learning." @default.
• W4317242512 created "2023-01-18" @default.
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• W4317242512 date "2022-12-11" @default.
• W4317242512 modified "2023-10-17" @default.
• W4317242512 title "Systematic Analysis of Big Data Based Machine Learning Algorithms on Various Fields" @default.
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• W4317242512 doi "https://doi.org/10.1109/tocs56154.2022.10015981" @default.
• W4317242512 hasPublicationYear "2022" @default.
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