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Talking about the nature of data warehouse and data mining

Data warehouse and data mining are two big concepts. They are very mature in foreign countries. In China, with the accumulation of enterprise data and the maturity of ERP in the past few years, data warehouse and data mining have started. How to establish a data warehouse and data mining is a problem that deserves constant discussion and optimization, not only in

Deswik Software Suite v2.0 win32_63 1CD (mining software)

Deswik Products:Deswik Software Suite v2.0 win32_63 1CD (mining software)Deswik Mining Consultants is an international company that provides innovative mining engineering and geological services. We also produce cutting-edge mine planning skills in the field of combined mining technology, from eachDepartment, specializ

Thoughts ----- mining Weibo sentiment analysis-mysql tutorial

A friend wants to capture and mine Sina Weibo as needed. In particular, this part of sentiment analysis facilitates his later experimental practices. In fact, text mining and analysis will produce greater results in the future. To give a simple example, everyone in the subway will refresh their circle of friends and friends every day. And these messages A friend wants to capture and mine Sina Weibo as needed. In particular, this part of sentiment anal

OracleODM Data Mining notes

I recently learned about Oracle Data Mining and found that there is very little information on the Internet. I suggest you sort it out by yourself. DataMiningPLSQLPackagesOracle Data Mining support I recently learned about Oracle Data Mining and found that there is very little information on the Internet. I suggest you do it yourself. Data

Microsoft Data Mining algorithm: Microsoft Neural Network Analysis Algorithm principle (9)

ObjectiveThis article continues our Microsoft Mining Series algorithm Summary, the previous articles have been related to the main algorithm to do a detailed introduction, I for the convenience of display, specially organized a directory outline: Big Data era: Easy to learn Microsoft Data Mining algorithm summary serial, interested children shoes can be viewed, Before starting the Microsoft Neural Network a

Mining external resources and making rational use of external resources

 The first: First is how we find out the chain of resources, then here I introduce three methods. 1, is the peer site outside the chain of the chain of mining methods. 2, search the instructions of the mining method. 3, online collection of mining methods. Then we will give you a detailed interpretation of these three methods. 1, is the peer site outside the

Summary: Data Mining: three categories and six items

Data Mining可分为三大类六分项来说明: Classification和Clustering属于分类区隔类; Regression和Time-series属于推算预测类; Association和Sequence则属于序列规则类。 Classification是根据一些变量的数值做计算,再依照结果作分类。(计算的结果最后会被分类为几个少数的离散数值,例如将一组数据分为"可能会响应"或是"可能不会响应"两类)。Classification常被用来处理如前所述之邮寄对象筛选的问题。我们会用一些根据历史经验已经分类好的数据来研究它们的特征,然后再根据这些特征对其他未经分类或是新的数据做预测。这些我们用来寻找特征的已分类数据可能是来自我们的现有的客户数据,或是将一个完整数据库做部份取样,再经由实际的运作来测试;譬如利用一个大型邮寄对象数据库的部份取样来建立一个Classification Model,再利用这个Model来对数据库的其它数据或是新的数据作分类预测。 Clustering用在将数

Hadoop mahout Data Mining Video tutorial

Hadoop mahout Data Mining Practice (algorithm analysis, Project combat, Chinese word segmentation technology)Suitable for people: advancedNumber of lessons: 17 hoursUsing the technology: MapReduce parallel word breaker MahoutProjects involved: Hadoop Integrated Combat-text mining project mahout Data Mining toolsConsulting qq:1840215592Course IntroductionThis cour

Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Time Series algorithm)

Reprint: http://www.cnblogs.com/zhijianliutang/p/4021799.htmlObjectiveThis 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 res

Bitcoin study of the---PPS and pplns mining model introduction

Introduction of PPS and PPLNS mining modelBitcoin generates a chunk every 10 minutes, and tens of thousands of people compete, and the chunk ends up being owned by only 1 people, and everyone else is out of business. You may have to dig for 5 years to get a chunk. Team mining is, once a team of anyone to obtain a block, the chunk of the currency according to the performance of everyone, so that everyone can

Hadoop mahout Data Mining Video tutorial

Hadoop mahout Data Mining Practice (algorithm analysis, Project combat, Chinese word segmentation technology)Suitable for people: advancedNumber of lessons: 17 hoursUsing the technology: MapReduce parallel word breaker MahoutProjects involved: Hadoop Integrated Combat-text mining project mahout Data Mining toolsConsulting qq:1840215592650) this.width=650; "src="

Bitcoin development Project (principle and development direction of mining)

Block chain enthusiasts (qq:53016353) block chain mining development direction Mining development is closely related to the development of Bitcoin, a brief review of mining history we can see these changes: 1. Block chain to the beginning of the 2013, the boundary, the entire history of mining can be divide

HDU 2448 Mining Station on the Sea (minimum cost flow +SPFA, Super n Times)

Mining Station on the SeaTime limit:5000/1000 MS (java/others) Memory limit:32768/32768 K (java/others)Total submission (s): 2572 Accepted Submission (s): 775Problem DescriptionThe Ocean is a treasure house of resources and the development of human society comes to depend D more on it. In order to develop and utilize marine resources, it's necessary to build mining stations on the sea. However, due to sea

Differences between data mining and Statistics (Guide to intelligent data analysis study notes)

When it comes to data mining, we tend to focus on algorithms during modeling while ignoring other steps. In real world data mining projects, other steps are the key to determining project success or failure. Guide to intelligent data analysis is the book recommended by the knime official website (http://tech.knime.org/guide-to-intelligent-data-analysis), according to the CRISP-DM process describes the proce

Summary of ten algorithms of data mining--core idea, algorithm advantages and disadvantages, application field

------------------------------------------------------------------------------------Welcome reprint, please attach the linkhttp://blog.csdn.net/iemyxie/article/details/40736773------------------------------------------------------------------------------------The algorithms in this paper only summarize the core idea. Detailed implementation details refer to this blog "Data Mining Algorithm learning" classification of other articles, not regularly upda

[resource-] Python Web crawler & Text Processing & Scientific Computing & Machine learning & Data Mining weapon spectrum

Reference:http://www.52nlp.cn/python-%e7%bd%91%e9%a1%b5%e7%88%ac%e8%99%ab-%e6%96%87%e6%9c%ac%e5%a4%84%e7%90%86 -%e7%a7%91%e5%ad%a6%e8%ae%a1%e7%ae%97-%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0-%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e% 98A Python web crawler toolsetA real project must start with getting the data. Regardless of the text processing, machine learning and data mining, all need data, in addition to through some channels to buy or download professional da

Data mining tools: Who is most suitable for CRM

It's been years since I last ventured to answer "How to choose Data Mining Tools". This article mainly elaborates the following two core viewpoints: 1. There is no best tool, or rather, the best tool for everyone. 2. The most useful tools are those that can meet the vast majority of data mining tasks you need. The main data mining tasks Most data-

Text mining using Uima and DB2 intelligent Miner

Gain more value from unstructured information. Study how a simple text mining application uses the UIMA SDK to build a text analysis engine to look for names in a document. Another UIMA component then writes the result to a table in the db2® database. This data is then used to use DB2 intelligent Miner to find strong associations between people who are often mentioned in the document. Brief introduction There is a growing desire to use information t

Machine learning and data mining

Problems:Classification, clustering, Regression, Anomaly Detection, association rules,Reinforcement learning, Structurd prediction, Feature Learning, Online learning,Semi-supervised Learning, Grammar inductionSupervised Learning:Decision Trees, ensembles (Bagging, boostring, Random Forest), k-mn, Linear regression,Native Bayes, nenural networks, Logistic regression, Perceptron,Support Vector Machine (SVM), Relevance vector machine (RVM)Clustering:BIRCH, Hierachical, K-means, Expectation-maximiza

Implementation of mining--apriori algorithm for GIS Information Association rules (next)

modification in the manner of processing, the code does not need to change the big.= = There is no way, after all, not everyone will write code ... )namespace fmanage{public partial class Analy:form {private system.windows.forms.checkbox[] Checkboxfactor S Private DataSet DS; Private int[] rowtables; Private int[] Flag; Private int[] dimention; Private int[] fee; private int p; Public Analy () {InitializeComponent (); This.p

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