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The fate and impact of large data characteristics on statistical applications

Abstract: This article discusses the medical large data (above) and discusses the medical large data (middle). The uniqueness of large data characteristics to statistical applications and the unique impact of large data challenges the traditional statistical methods, stimulating new, suitable for large data analysis of statistics This paper discusses the medical large data (on) and the Medical large data (middle). The uniqueness of large data characteristics to the fortune and impact data in statistical applications challenges the traditional statistical methods and stimulates the development of new statistical methods suitable for large data analysis. This article mentioned some of the encounters and problems, a ...

Application of content analysis in user feedback analysis

* The content of this article by the Ferry, Sword Rainbow, and the author together to provide, the author summarized TB recently in various key products and shopping processes have joined the user feedback portal (Figure 1), also opened a variety of official forums to collect user opinions and suggestions, so will collect a large number of plain text data. How do you analyze these data to guide product improvement? This article will describe the theoretical basis and practical application of content analysis (content-analysis) in the processing of network text data (e.g., user feedback). Including: The content analysis method brief, the enterprise application content analysis Step ...

Cloud Large Data Forum: Exploring the social ecology of large data

Moderator: I am honored to introduce the first speaker, Professor Zhujianhua from the City University of Hong Kong. I wish teachers in the United States and Hong Kong have a long working experience, for the dissemination of sociology has a deep attainments. The subject of his speech today is a large figure in the eyes of a liberal arts professor. Please。 Zhujianhua: Thank you for the introduction of teacher Zhou, with the current network language, I am a liberal arts man, or an old man of liberal Arts. Most recently, the most impressive thing is Mo Yan's acceptance of the Nobel award, saying that literature is not science and literature is useless. I want to explain that literature is not equal to Uvenko, liberal arts ...

Harford: Big data, or big mistakes?

Large data is a vague expression of large-scale phenomena.   The term has now been overheated by entrepreneurs, scientists, governments and the media. Five years ago, a Google research team announced a remarkable achievement in the world's top science magazine Nature. The team can track the spread of flu in the United States, which does not depend on any medical examination. They are tracking even faster than the CDC. Google's tracking results are only a day's delay, and the CDC needs to compile a large number of physicians ' diagnoses to get a spread of the trend chart ...

"Book pick" large data development of the first knowledge of Hadoop

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

Large Data Technology stickers: Building a guided data mining model

The purpose of data mining is to find more quality users from the data. Next, we continue to explore the model of the guidance data mining method. What is a guided data mining method model and how data mining builds the model. In building a guided data mining model, the first step is to understand and define the target variables that the model attempts to estimate. A typical case, two-dollar response model, such as selecting a customer model for direct mailing and e-mail marketing campaigns. The build of the model selects historical customer data that responds to similar activities in the past. The purpose of guiding data mining is to find more similar ...

Big Data Gold rush is cool, but the method is blind

This article originally contained the FT website, original title: Big Data:are We making a big mistake, it seems that I saw a bit late, but still share it. Because it does discuss some of the issues I've been thinking about recently, it's a speculative article.   If you've never known big data before, this can be considered a primer. This article is only opinion, because the query is more simple than the proof, but the big data is now hot, these negative comments, if as a conversation to collect, is also good ...

Large Data Technology stickers: Building a guided data mining model

The purpose of data mining is to find more quality users from the data. Next, we continue to explore the model of the guidance data mining method. What is a guided data mining method model and how data mining builds the model. In building a guided data mining model, the first step is to understand and define the target variables that the model attempts to estimate. A typical case, two-dollar response model, such as selecting a customer model for direct mailing and e-mail marketing campaigns. The build of the model selects historical customer data that responds to similar activities in the past. The purpose of guiding data mining is to find more classes ...

China with "Big data"

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

China with "Big data"

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

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