Adaptation of Classical Machine Learning Algorithms to Big Data Context: Problems and Challenges : Case Study: Hidden Markov Models Under Spark
Published: Oct 1, 2019
Abstract
Big Data Analytics presents a great opportunity for scientists and businesses. It changed the methods of managing and analyzing the huge amount of data. To make big data valuable, we often use Machine Learning algorithms. Indeed, these algorithms have shown, in the past, their processing speed, efficiency and accuracy. But today, with the complex characteristics of big data, new problems have emerged and we are facing new challenges when...
Paper Details
Title
Adaptation of Classical Machine Learning Algorithms to Big Data Context: Problems and Challenges : Case Study: Hidden Markov Models Under Spark
Published Date
Oct 1, 2019
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History