ssas data mining

Recently, I have the opportunity to access some data mining things.I personally feel that this technology will certainly have a great development prospect.So I will use this article to explain my views on data mining.The concept of data mining is explained step by step. (1)

Data Mining-association analysis frequent Pattern Mining Java and C + + implementations of Apriori, Fp-growth, and Eclat algorithms:Website: http://blog.csdn.net/yangliuy/article/details/7494983Data Mining-Java implementation of newsgroup18828 text classifier based on Bayesian algorithm and KNN algorithm (top)http://bl

as the Greenplum database and HAWQ. 　　 The maintenance activities performed are open to the Apache community and ongoing academic research. 　　 If you only summarize the features of Madlib in one sentence, as described in the title, you can use SQL to play data analysis, data mining, and machine learning. 　　 2. Features 　　 (1) Classification 　　 If the desired out

I statistics Department data Mining direction, has been using the Python implementation algorithm, then the introductory textbook is "machine learning combat", which is also used in Python. But recently found that the recruitment requirements of data mining engineers generally have Java, and the NPC

Today found a very good blog (http://www.RDataMining.com), Bo Master is committed to research the R language in data mining applications, just recently want to learn a system of r language and data mining the entire process, read the content of this blog, the heart of a long time can not calm. The decision starts today

Brief introduction In the two articles before the "Data mining with WEKA" series, I introduced the concept of data mining. If you haven't read data mining with Weka, part 1th: Introduction and regression and

Today I saw in this article how to choose the model, feel very good, write here alone.More machine learning combat can read this article: http://www.cnblogs.com/charlesblc/p/6159187.htmlIn addition to the difference between machine learning and data mining,Refer to this article: https://www.zhihu.com/question/30557267Data mining: Also known as

JlqingData Mining-association analysis frequent Pattern Mining Java and C + + implementations of Apriori, Fp-growth, and Eclat algorithms:Website: http://blog.csdn.net/yangliuy/article/details/7494983Data Mining-Java implementation of newsgroup18828 text classifier based on Bayesian algorithm and KNN algorithm (top)http://blog.csdn.net/yangliuy/article/details/74

Http://www.cnblogs.com/captain_ccc/articles/4093652.html This article is also the continuation of the Microsoft Series Mining algorithm Summary, the previous several mainly based on state discrete value or continuous value for speculation and prediction, the main algorithm used is three: Microsoft Decision tree Analysis algorithm, Microsoft Clustering Analysis algorithm, Microsoft Naive Bayes algorithm , of course, the follow-up also added a result

: Published in 2012, corresponding to Mahout version 0.5, is currently mahout the latest book books. At present, only English version, but a bit, the inside vocabulary is basically a computer-based vocabulary, and map and source code, is suitable for reading.? IBM mahout Introduction: http://www.ibm.com/developerworks/cn/java/j-mahout/Note: Chinese version, update is time for 09, but inside for Mahout elaborated more comprehensive, recommended reading, especially the final book list, suitable fo

Just a few, say something:Basic article:1. Reading "Introduction to Data Mining", this book is very easy to understand, there is no complex advanced formula, very suitable for people to get started. You can also use this book for reference "Data mining:concepts and Techniques". The second is thicker, but also a bit more knowledge of

Defined Data Mining is the nontrivial process of acquiring effective, novel, potentially useful, and ultimately understandable patterns from large amounts of data stored in databases, data warehouses, or other repositories. What is the use of. Data

JournalsACM TKDD http://tkdd.cs.uiuc.edu/DMKD http://www.springerlink.com/content/1573-756X/?p=859c3e83455d41679ef1be783e923d1dpi=0IEEE Tkde http://www.ieee.org/organizations/pubs/transactions/tkde.htmACM TODS http://www.acm.org/tods/VLDB Journal http://www.vldb.org/ACM Tois http://www.acm.org/pubs/tois/ConferencesSIGKDD http://www.sigkdd.org/ICDM http://www.cs.uvm.edu/~icdm/SDM http://www.siam.org/meetings/sdm08/PKDD http://www.ecmlpkdd2008.org/VLDB http://www.vldb.org/Sigmod http://www.acm.org

Validating a data mining model Typically, for a particular case, we can't pinpoint which mining algorithm is the most accurate, so we define multiple mining models in a mining structure, and we get the most accurate one by validating multiple

The algorithm in this paper only outlines the core idea, the specific implementation details of this blog "Data Mining Algorithm learning" classification under other articles, not regularly updated. Reprint please indicate the source, thank you.Referring to a lot of information and personal understanding, the ten algorithms are categorized as follows:? Classification algorithm: C4.5,cart,adaboost,naivebayes

development of Baidu, Google. But with the rise of big data in recent years, crawler applications have been elevated to unprecedented heights. In terms of big data, in fact, their own data or user-generated data platform is very limited, only like e-commerce, micro-bo such a platform to avoid strong self-sufficiency,