weka datasets

When you use Experimenter in Weka to connect to the Mysql database, the default link is jdbc: idbexperiments: When you use Experimenter in Weka to connect to the Mysql database, the default link is jdbc: idb = experiments: When you use Experimenter in Weka to connect to the Mysql database, the default link is: Jdbc: idb = experiments. GP Change it: Jdbc: mys

Every day must record their own little bit, not recorded, after a period of time will forget, forget is equal to have not experienced. I can't go on like this every day. I want to have a plan, have a dream, the pursuit of excellence, the achievement is different.Today I started my study Weka road. When I was learning, I was questioning, why should I learn Weka? Is it just for the students in the study to sh

1) data input and outputWOW (): View the parameters of the Weka function.Weka_control (): Sets the parameters of the Weka function.Read.arff (): reads the data weka attribute-relation File format (ARFF).Write.arff: Writes data to Weka attribute-relation file format (ARFF).2) Data preprocessingNormalize (): Unsupervised

First step: Create a new Java project, New->javaproject, assuming the project is named WekatestStep Two: Import Weka.jarStep three: src correlationAfter the import there are many. class files, directly double-click Open is not see the code, you need to the Weka folder to extract a compressed package called Weka-src.jarThe diagram on the left is the. class file that you see after importingOn the left, ctrl-c

Brief introduction In data mining with WEKA, part 1th: Introduction and regression, I introduced the concept of data mining and free open source software Waikato Environment for Knowledge Analysis (WEKA), which can be used to mine data to obtain trends and patterns. I also talked about the first method of data mining-regression-using it to predict numeric values based on a given set of input values. This a

1, first download installation WekaHttp://www.cs.waikato.ac.nz/ml/weka/downloading.html2. Open the Weka and select the first explorer3, prepare the data set file, in Weka, the general data file is: Xxx.arff, for example, I edit a file called Tumor.arff, the contents of the file is:@RELATION tumor@ATTRIBUTE size NUMERIC@ATTRIBUTE ' Class ' {' 1 ', ' 0 '}@DATA0.0,

Package linearregression; import WEKA. classifiers. evaluation; import WEKA. classifiers. functions. linearregression; import WEKA. core. instance; import WEKA. core. instances; import WEKA. core. converters. converterutils. datasource; public class legression {/*** @ Param

Rweka(http://cran.r-project.org/web/packages/RWeka/index.html):1) data input and outputWOW (): View the parameters of the Weka function.Weka_control (): Sets the parameters of the Weka function.Read.arff (): reads the data weka attribute-relation File format (ARFF).Write.arff: Writes data to Weka attribute-relation fil

search.Subsetsizeforwardselection: Forward linear search by feature subset size, which is an extension of linear search.Tabusearch: Taboo Search.subset Search Methods:1. Bestfirst2. Greedystepwise3. Fcbfsearch (ASU)subset Evaluation Methods:1. Cfssubseteval2. Symmetricaluncertattributeseteval (ASU)individual Search Methods:1. Rankerindividual Evaluation Methods:1. Correlationattributeeval2. Gainratioattributeeval3. Infogainattributeeval4. Onerattributeeval5. Principalcomponents (used with a ran

Q, then for each q has q from the object P direct density can be reached.(3) algorithm flowMain flow: input e,minopt and object set nI, find an unmarked core object K, and set this object as marked, if the core object cannot be found to exit directlyII. Extend this core object, expand (k)III. If all objects are marked, exit, otherwise turn IExpand process: Input Core Object KI, initialize a set of S, put in KII. Iterate over the collection element, and for each core object in the collection, fi

The 1NN nearest neighbor algorithm for machine learning, called IB1 in Weka, is because instance base 1, which is a lazy learning algorithm based only on an instance of the nearest neighbor.The following summarizes, Weka in the IB1 source of learning summary.First, you need to introduce Weka-src.jar to the compilation path, otherwise you cannot track the source c

Feature selection, I am not familiar with this part, probably say, withattributeselection for feature selection, it needs to be set 3 Aspects, First: Class for attribute evaluation (self to weka software Look in English attribute Evaluator ), second: the Way to search (self to weka See in the software, English search Method ), Third: It is the data set that you want to perform the feature selection. Fin

Author: finallyliuyu reprinted and used. Please specify the source. In the previous section, the VSM model of kmeans text clustering provides how to establish a document vector model and write the data format ARFF required by WEKA software.Code. Here we will introduce how to obtain the clustering center from WEKA and complete the clustering code. As for how to use

I personally think we can directly discuss data mining.AlgorithmAnd WEKA are too impatient to use. I learned data mining methods directly from the beginning. Some methods are difficult and boring. What I often think about is not the method itself, but "What is this ?". After WEKA is used, some things gradually become clearer, because the input and output give people a very intuitive feeling, and the learn

It should be difficult to use WEKA for a m training set: 1. Increase the memory size. In fact, WEKA can not only use physical memory, but also occupy virtual memory. If the available memory of Java is set to 2 GB, if the physical memory of the machine is only 1 GB, the operating system will automatically divide a block on the hard disk as the virtual memory as needed. However, this process is generally slo

When importing data with Weka, the reportJava.lang.reflect.InvocationTargetExceptionError, the Weka run package did not give detailed error information and could not be found.Direct debugging Weka Source code, found m_maxc=infinity, it seems that the data has illegal characters.Sure enough, look at this field is a numeric type, how can have infinity.It seems to e

Label:Weka connect the database around a lot of circles, always because of some messy reasons not connected. The detailed process is now written to save time for those who use it later.1. Configure the environment (by default, the JDK is already configured).Create a new Lib directory under the Weka installation directory and copy the database driver for JDBC (jar package) into the \libVariable: Weka_home value: D:\