data mining with rattle and r

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"Reading notes-data mining concepts and technologies" data warehousing and online analytical processing (OLAP)

Before we saw the data and the preprocessing of the data, where was the data after processing? Put it in a place called "Data Warehouse".Basic concepts of data warehousing: Definition of Data Warehouse-topic-oriented, int

Case: Oracle dul Data Mining non-regular recovery drop deleted data table without backup

reached-logical Record Count 960Commit Point reached-logic Al Record Count 1024Commit Point reached-logical Record Count 1088Commit Point reached-logical Record Count 1152Commit point reached-logical Record Count 1216Commit Point Reached-lo Gical Record Count 1280Commit point reached-logical Record Count 1344Commit point reached-logical Record Count 1408Com MIT point reached-logical Record Count 1472Commit point reached-logical Record Count 1536Commit Point Reached-logica L Record Count 1600Com

Case: Oracle dul Data Mining No database backup unconventional recovery truncate deleted data table

T_xifenfei_1 (OWNER VARCHAR2 (), object_name VARCHAR2 (+), Subobject_name VARCHAR2 (+), object_id Number,data_object _id Number,object_type VARCHAR2 (+), CREATED date,last_ddl_time date,timestamp VARCHAR2 (+), STATUS VARCHAR2 (7), TE Mporary VARCHAR2 (1), GENERATED VARCHAR2 (1), SECONDARYVARCHAR2 (1), NAMESPACE number,edition_name VARCHAR2 ()) STORA GE (Dataobjno 68332);. Unloading table T_XIFENFEI_1DUL:Warning:Recreating file "T_xifenfei_1.ctl" 67854 rows unloadedAdditional notes:1. In the lat

Exploring Bi Data Mining

What is data mining? Data mining, also known as knodge DGE discovery, is an automatic or semi-automated method to find potential and valuable information and rules in data. Data Min

Microsoft Data Mining algorithm: Microsoft Linear regression analysis Algorithm (11)

ObjectiveThis 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 fu

Summary of 18 Classic data mining algorithms

Summary of 18 Classic data mining algorithmsAll the data mining code involved in this article has been put on my github.Address Link: https://github.com/linyiqun/DataMiningAlgorithmIt took about 2 months to learn the classic algorithm of 18 big data

"Reading notes-data mining concepts and techniques" data preprocessing

original data Overview of Data Protocol policies Dimensional regression Quantity specification Data compression Wavelet transform--linear signal processing technology, suitable for high dimensional data (HTTP://HI.BAIDU.COM/QINGSHUANGCII/ITEM/31E8831E65350DDE64EABF4C)

Naive Bayes algorithm for Data Mining

Recently, I have read some data mining materials to understand and study the classification technology in the data mining process. 1. Data Mining overview data

Common Data Mining Methods

Common methods of data mining basic concepts data mining is to extract hidden, unknown, and the process of potentially useful information and knowledge. Common methods of data mining basic concepts

Learning Note: Oracle dul data Mining export oracle11g data file in table in bad block

risky, hands-on need to be cautious Oracle Research Center http://www.oracleplus.net This article by the master cherish the original sharing, reproduced please try to retain the site website--------------------------------------ORACLE-DBA----------------------------------------The most authoritative and professional Oracle Case Resource Summary Study NOTE: Oracle Dul Data Mining export oracle11g

Data Mining and R Language

Original Title: Data Mining with R: learning with case studies Author: (Portuguese) Lu ís torgo Translator: Li Hongcheng Chen daolun Wu liming series name: computer Science Series Publishing House: Mechanical Industry Publishing House ISBN: 9787111407003 Release Date: April 2013 publication date: 16 open pages: 1: 1-1 category: Computer> database storage and management For more information,

"Data mining: R Language Combat" chapter II Data overview

2.1 n*m Data SetIn a dataset in the form of N*m, n represents the row of the data, that is, the number of observation points, and M represents the column, that is, the number of variables; N*m is the dimension of the data.In general, when getting a piece of data, the first thing to do is to look at the number of observations, the number of variables, and the actu

Apriori algorithm of Data Mining Association rules

Apriori algorithm is a basic algorithm of big data in association rules. The association rule Mining algorithm was proposed by Rakesh Agrawal and Ramakrishnan Srikant two PhD in 1994. The purpose of association rules is to find out the relationship between items and items in a data set, also known as shopping blue analysis, because "Shopping blue analysis" aptly

Python Data Mining and machine learning technology Getting started combat __python

Summary: What is data mining. What is machine learning. And how to do python data preprocessing. This article will lead us to understand data mining and machine learning technology, through the Taobao commodity case data preproces

"Bi thing" analysis of 13 kinds of commonly used data mining technology

The original: "Bi thing" analysis of 13 kinds of commonly used data mining technologyFirst, the forefrontData mining is from a large number of incomplete, noisy, fuzzy, random data, the extraction of hidden in it, people do not know beforehand, but also potentially useful information and knowledge of the process. The t

Commodity recommendation using association rules of SQL Server Analysis Services data mining (5)

If you have a shopping website, how do you recommend products to your customers? This function is available on many e-commerce websites. You can easily build similar functions through the data mining feature of SQL Server Analysis Services. This article mainly demonstrates how to organize data according to the requirements of tools, and then perform

Data Mining concepts and techniques (Han Jiawei) reading notes 4--data integration and transformation

calculated as follows:where n is the number of data ancestors, COUNT (A=ai) is the number of Ganso with value AI, and count (B=BJ) is the number of Ganso with value BJ.3. Meta-ancestor redundancy detection repetitionInconsistencies usually occur between various replicas, in which the input errors and portions of the updated data appear without updating all occurrences.4. Detection and processing of

Data analysis and mining-PHP Tutorial

Data analysis and mining. Data Analysis and Mining Baidu MTC is an industry-leading mobile application testing service platform that provides solutions to the costs, technologies, and efficiency problems faced by developers in mobile application testing. Data Analysis and

R Language Data Mining Combat series (1)

R Language Data Mining Combat (1)First, the basis of data miningData Mining : "Gold panning" from the data, extracting hidden, unknown, potentially valuable relationships, patterns, and trends from a large amount of data, includin

Beyond data Mining

The Predictive modeling community (predictive modeling community) applies data mining to artifacts from software projects. This work has been very successful, and we know how to build a predictive model for the impact and inadequacy of the software, and to build a predictive model for tasks such as the Developer programming model (see the extended version of this article for more information). That is to s

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