tools used for data mining

ObjectiveThis article is also the continuation of the Microsoft Series Mining algorithm Summary, the first few mainly based on state discrete values or continuous values for speculation and prediction, the algorithm used mainly three kinds: Microsoft Decision tree Analysis algorithm, Microsoft Clustering algorithm, Microsoft Naive Bayes algorithm , of course, followed by a summary of the results of the pred

Reprint: http://www.cnblogs.com/zhijianliutang/p/4009829.htmlThis article is mainly to continue the previous Microsoft Decision tree Analysis algorithm, the use of another analysis algorithm for the target customer group mining, the same use of Microsoft case data for a brief summary.Application Scenario IntroductionIn the previous article, we used the Microsoft

Data Warehouse and data mining--a sharp weapon to participate in the competition of digital telecommunication enterprises The solution of Guangdong Telecom Data Warehouse based on Sybase Guangdong Institute of Telecommunication Science and technology 1 overview With the opening of the telecom market, the competition

Data mining is the process of finding patterns in a given data set. These patterns can often provide meaningful and insightful data to whoever are interested in that data. Data mining i

Tags: style blog http io color ar os for SPOriginal: (original) Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Time Series algorithm)ObjectiveThis article is also the continuation of the Microsoft Series Mining algorithm Summary, the first few mainly based on state d

Common Data Mining MethodsBasic Concepts Data Mining is fromMassive, incomplete, noisy, and fuzzyThe process of extracting potentially useful information and knowledge hidden in the data that people do not know beforehand. Specifically, as a broad application-oriented cross-

data mining tools, data mining personnel may be fascinated by a large number of segmentation results, while ignoring the purpose of segmentation, and business personnel may think that these subdivisions are conclusive, can not be adjusted. The best approach should be the cl

small data samples, mainly used in user experience surveys; quantitative analysis is a method to test and prove certain things using large data samples. It is mainly used for user behavior data analysis.1.2 data analysis and

key points. The slow change dimension starts from the maintainability of the specific implementation process. a more unified and common method can be used to increase the snapshot start time and snapshot end time, combined with the primary key of the business system, you can complete the key history snapshot view of the DSS layer real enterprise data. In the implementation process, the key is to grasp the

Http://www.cognoschina.net/club/thread-66425-1-1.html for reference only "Automatic Big Data Mining" is the true significance of big data. Nowadays, big data cannot work very well. Almost everyone is talking about big data. But what is big

Reprint: http://www.cnblogs.com/zhijianliutang/p/4067795.htmlObjectiveFor some time without our Microsoft Data Mining algorithm series, recently a little busy, in view of the last article of the Neural Network analysis algorithm theory, this article will be a real, of course, before we summed up the other Microsoft a series of algorithms, in order to facilitate everyone to read, I have specially compiled a