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Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Sequential analysis and Clustering algorithm)

Tags: article vs2008 reg knowledge View HTM new research will notObjective This 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 al

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

... If you want to buy a car, you have to have money.Accuracy VerificationFinally, let's verify the accuracy of today's clustering algorithm, and what is the difference between the decision tree algorithms in the previous article, we click into the data Mining accuracy chart:We can see that today's cluster analysis algorithm, the score is 0.72, than the previous decision tree algorithm 0.87, or a slight gap, of course, can not only score to evaluate

More than 20 big data tools commonly used by Java to Adult College data people

Recently I asked a lot of Java developers about what big data tools they used in the last 12 months.This is a series of topics for: Language Web Framework Application Server SQL data Access Tool SQL database Big Data Build tools Cloud Pro

Solve 20% of big data problems

A modular big data platform can solve 80% of the big data problems. To solve the other 20% of the problems, big data platform vendors must meet the special needs of industry customers for customized development. ZTE's DAP 2.0

Easily learn multithreading (I) -- the big data era requires multithreading and the multi-threaded data Era

Easily learn multithreading (I) -- the big data era requires multithreading and the multi-threaded data Era In the demand for big data and high concurrency, how can we make our enterprise survive and survive in the harsh environment of competition? This avoids writing concur

Data sharding in Big Data graph database

Excerpted from Chapter 14 "Big Data daily notice: Architecture and algorithms", the book directory is here for massive data to be mined, in a distributed computing environment, the first problem is how to evenly distribute data to different servers. For non-graph data, this

Data storage in the Big Data era, non-relational database MongoDB (i) (RPM)

Source: http://www.cnblogs.com/mokafamily/p/4076954.htmlThe explosive development of NoSQL technology  For a long time in the past, relational databases (relational database Management System) have been the most mainstream database solution, He uses things and relationships in the real world to explain the abstract data architecture in the database. However, in the explosive development of information technology today,

Data storage in the Big Data era, non-relational database MongoDB

For a long time in the past, relational databases (relational database Management System) have been the most mainstream database solution, He uses things and relationships in the real world to explain the abstract data architecture in the database. However, in the explosive development of information technology today, big data has become the cloud computing, the

Data storage in the Big Data era, non-relational database MongoDB

Http://db-engines.com/en/rankingTransferred from: http://www.cnblogs.com/mokafamily/p/4076954.htmlThe explosive development of NoSQL technology  For a long time in the past, relational databases (relational database Management System) have been the most mainstream database solution, He uses things and relationships in the real world to explain the abstract data architecture in the database. However, in the explosive development of information technolo

Jdbc BASICS (3) Big text, binary data processing, and jdbc Data Processing

Jdbc BASICS (3) Big text, binary data processing, and jdbc Data Processing LOB (Large Objects)Divided:CLOBAndBLOBBig text and big binary data CLOB: used to store large text BLOB: used to store binary data, such as images, sounds,

Big Data paging solution and data paging Solution

Big Data paging solution and data paging Solution 1. Writing PurposeThe paging solution is proposed to solve the performance problem when the system needs to retrieve the big data list.2 terms, definitions, and abbreviations 3. Performance Analysis of Large

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

Original: (original) Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Naive Bayes algorithm)This article is mainly to continue on the two Microsoft Decision Tree Analysis algorithm and Microsoft Clustering algorithm, the use of a more simple analysis algorithm for the target customer group mining, the same use of

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

of the most want to buy a car of the characteristics of the silver, tomorrow continue to analyze, and see can help me to simple analysis, the same first a few of the structure of the picture:Tomorrow night the results are analyzed, and the characteristics of the two algorithms are compared and analyzed. Be interested in big data don't forget your "recommendation" Oh.The power of

Socket -- accept big data, socket -- accept data

Socket -- accept big data, socket -- accept dataI. Simple ssh Functions   1.1 implement functions In the previous blog, we have implemented a simple small program similar to the Linux Server ssh function. You can enter a system command to return the command running result. Today we will start with this, let's see how the socket can accept a large amount of data.

Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Linear regression analysis algorithm)

Reprint: http://www.cnblogs.com/zhijianliutang/p/4076587.htmlThis is the last article of the Microsoft Series Mining algorithm, after the completion of this article, Microsoft in Business intelligence this piece of the series of mining algorithms we have completed, this series covers the Microsoft in Business Intelligence (BI) module system can provide all the mining algorithms, of course, this framework can be fully expanded, You can customize the mining algorithm, but the current series is not

Java's Big Data bitmap method (no repeating sort, repeating sort, de-duplication, data compression)

the Java implementation of the Big Data bitmap method (no repetition , repetition, deduplication, data compression)Introduction to Bitmap methodThe basic concept of a bitmap is to use a bit to mark the storage state of a data, which saves a lot of space because it uses bits to hold the

2016 Big data spark "mushroom cloud" action spark streaming consumption flume acquisition of Kafka data DIRECTF mode

Liaoliang Teacher's course: The 2016 big Data spark "mushroom cloud" action spark streaming consumption flume collected Kafka data DIRECTF way job.First, the basic backgroundSpark-streaming get Kafka data in two ways receiver and direct way, this article describes the way of direct. The specific process is this:1, dire

Big data backup and recovery application case-back up and restore data through a partitioned table

Big data backup and recovery application case-the business features of OLAP databases through partitioned table backup and restoration of massive data backup and recovery solutions are to load batch data into the database, then analyze and process the data.

. NET BULK insert data into SQL Server database, SqlBulkCopy class BULK insert big data into database

; Sqlbulkcopy.bulkcopytimeout=bulkcopytimeout; for(inti =0; i ) {sqlbulkCopy.ColumnMappings.Add (dt. Columns[i]. ColumnName, dt. Columns[i]. ColumnName); } sqlbulkcopy.writetoserver (DT); Sqlbulkcopy.close ();//Close Connection return true; } } Catch(System.Exception ex) {Throwex; } } /// ///BULK INSERT Data/// /// Connection Database String

Accurate data mining in the big Data era-using R language

data analysis visual image of JPEG format output;Case 3: How to use the R language for layering or cluster sampling to build training sets and test sets;Case 4: Use Ggplot2 to draw a variety of complex graphics.Second Lecture: Logistic regression and commercial big Data modelingLogistic regression is one of the most important

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