作者: Flora Amato , Mario Barbareschi , Valentina Casola , Antonino Mazzeo , Sara Romano
DOI: 10.1007/978-3-319-03889-6_14
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摘要: Nowadays, in a broad range of application areas, the daily data production has reached unprecedented levels. This origins from multiple sources, such as sensors, social media posts, digital pictures and videos so on. The technical scientific issues related to booming have been designated "Big Data" challenges. To deal with big analysis, innovative algorithms mining tools are needed order extract information discover knowledge continuous increasing growing. In most methods volume variety directly impact on computational load. this paper we illustrate hardware architecture decision tree predictor, widely adopted machine learning algorithm. particular show how it is possible automatically generate implementation predictor module that provides better throughput available software solutions.