| The rapid development of Internet technology has brought great growth of data volume.Traditional technology cannot handle these massive amounts of data according to business efficiency requirements.In those special industries like weather, remote sensing, geological disaster monitoring and so on, it is very important that valuable and understandable knowledge can be found out from the vast amounts of data in a more rapid, efficient and cost-effective way to help leaders make better decisions.Cloud computing technology first proposed by Google has a natural advantage in handling massive data andhas been widely applyed in recent years.Data mining technologybrings new opportunities for the development of cloud computing. Hadoop is an open source implementation of Google’s cloud computing platform.It handlesthese massive amounts of data with high performance and reliability.Based on deeply studying of traditional data mining algorithm,itis a hot topic how to optimize the algorithmonHadoop in order to deal with these massive amounts of data.In this paper, Based on Hadoop cloud platform using data mining technology to deal with the weather data are researched.Firstly,it deeply introduces the basic theory and knowledge of Hadoop cloud computing platform.It also elaboratesthe concepts and techniquesof data mining based on Hadoop, mainly focusing on Bayesian classification algorithm.then, it introduces the concept of correlation analysis and proposesan improved Naive Bayes algorithm based on Hadoop cloud platform and relevance determination applyingto weather forecast.Finally, it sets up a Hadoop cluster as test environment toverify the function and performanceof the improved algorithm.The analysis and comparison of the experimental results shows thatthe improved Naive Bayes algorithmbased on this design not only makes the classification and prediction results more reliable, but also greatly improves the efficiency of the algorithm and is suitable for processing the vast amounts of data. |
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