weka

Weka Linear regression ClassNotFoundException

由 ╄→尐↘猪︶ㄣ 提交于 2019-12-11 01:14:26
问题 String filePath = new File("").getAbsolutePath(); DataSource source = new DataSource(filePath + "\\src\\data\\data.arff"); Instances dataset = source.getDataSet(); // set class dataset.setClassIndex(0); // build model **LinearRegression lr = new LinearRegression();** lr.buildClassifier(dataset); System.out.println(lr); Right after LinearRegression instantiation I get this error: Exception in thread "main" java.lang.NoClassDefFoundError: no/uib/cipr/matrix/Matrix at weka_prediction.Main

Weka - differences between Explorer and Experimenter outcomes

由 泪湿孤枕 提交于 2019-12-11 01:04:18
问题 I just wondered why is the % correctly classified differs from the Explorer and Experimenter aspects of Weka. I have checked to ensure I am employing 10-cross fold validation as well as all other paramaters! Anyone have any ideas? Thanks 回答1: I have the solution, as provided by Mark Hall, as I emailed him on the Weka Mail list. Here is the difference between Explorer and Experimenter: The Experimenter operates differently from the Explorer. The Explorer sums evaluation metrics over the folds

Remove Missing Values in Weka

由 柔情痞子 提交于 2019-12-11 00:45:56
问题 I'm using a dataset in Weka for classfication that includes missing values. As far as I understood, Weka replaces them automatically with the Modes or Mean of the training data (using the filter unsupervised/attribute/ReplaceMissingValues ) when using a classifier like NaiveBayes. I would like to try removing them, to see how this effects the quality of the classifier. Is there a filter to do that? 回答1: My approach is not the perfect one because IF you have more than 5 or 6 attributes then it

Regarding RandomTree in Weka

由 一笑奈何 提交于 2019-12-10 21:09:58
问题 I was playing around with weka when I observed a minNum field in the RandomTree configuration. I read the description which said "The minimum total weight of the instances in a leaf". However, I couldn't really understand what it means. I played around with that number, and I realized that when I increase it, the size of the tree thus generated reduces. I couldn't correlate as to why this is happening. Any help/references will be appreciated. 回答1: This has to do with the minimum number of

Win7 系统中安装数据挖掘工作平台 Weka

由 早过忘川 提交于 2019-12-10 15:13:14
1.我的环境 操作系统：32位 Win7 旗舰版 Service Pack 1 2.下载WEKA OSC上WEKA的页面地址： http://www.oschina.net/p/weka 软件首页地址： http://www.cs.waikato.ac.nz/ml/weka/ 各版本Weka运行需要的Java版本，可以在这个页面找到： http://www.cs.waikato.ac.nz/ml/weka/requirements.html 该页面上的一张表格截图如下： 进入下载页面： http://www.cs.waikato.ac.nz/ml/weka/downloading.html 我的电脑是个32位Win7系统，并且之前并没有安装过Java虚拟机 因此我在下载时下载“Windows x86”分类中包括JavaVM1.7的包 单击粗体的“here”链接后，会前往SourceForge的对应页面下载 下载后的安装包文件名为weka-3-6-11jre.exe 3.安装Weka 双击weka-3-6-11jre.exe进入安装向导，单击“Next >”进入下一步 接下来是用户协议，GNU GENERAL PUBLIC LICENSE Version 2 这个协议的信息可以在下面这个页面看到： Version2.0： http://www.gnu.org/licenses/gpl

Weka normalizing columns

由 拥有回忆 提交于 2019-12-10 13:25:25
问题 I have an ARFF file containing 14 numerical columns. I want to perform a normalization on each column separately, that is modifying the values from each colum to ( actual_value - min(this_column)) / (max(this_column) - min(this_column) ). Hence, all values from a column will be in the range [0, 1] . The min and max values from a column might differ from those of another column. How can I do this with Weka filters? Thanks 回答1: This can be done using weka.filters.unsupervised.attribute

Finding a correlation between variable and class variable

由 别等时光非礼了梦想. 提交于 2019-12-10 11:44:12
问题 I have a dataset which contains 7 numerical attributes and one nominal which is the class variable. I was wondering how I can the best attribute that can be used to predict the class attribute. Would finding the largest information gain by each attribute be the solution? 回答1: So the problem you are asking about falls under the domain of feature selection, and more broadly, feature engineering. There is a lot of literature online regarding this, and there are definitely a lot of blogs

Which Weka and LibSVM .jar files to use in Java code for SVM classification

由 半腔热情 提交于 2019-12-10 10:12:46
问题 If I use Weka Explorer to run some training data against testing data using SVM with a linear kernel, everything is fine. But I need to do this programmatically in my own Java and my current code looks like this: Instances train = new Instances (...); train.setClassIndex(train.numAttributes() - 1); Instances test = new Instances (...) + ClassificationType classificationType = ClassificationTypeDAO.get(6); LibSVM libsvm = new LibSVM(); String options = (classificationType.getParameters());

Unable to execute jar file despite having PATH and CLASSPATH set

由 删除回忆录丶 提交于 2019-12-10 04:35:11
问题 My question is regarding including jar files in path. It has 2 parts. 1) I am trying to execute weka.jar jar file located in /home/andy/software/weka/weka.jar PATH variable points to this jar file (i.e. to /home/andy/software/weka/weka.jar) and so does CLASSPATH. However when I try to run the jar using java -jar weka.jar, I get an error "Unable to access jarfile weka.jar". Any ideas what is going on? I am on Ubuntu Linux. I looked around in SO and it seems like I am not doing anything that is

Simple text classification using naive bayes (weka) in java

由 馋奶兔 提交于 2019-12-10 04:35:09
问题 I try to do text classification naive bayes weka libarary in my java code, but i think the result of the classification is not correct, i don't know what's the problem. I use arff file for the input. this is my training data: @relation hamspam @attribute text string @attribute class {spam,ham} @data 'good',ham 'good',ham 'very good',ham 'bad',spam 'very bad',spam 'very bad, very bad',spam 'good good bad',ham this is my testing_data: @relation test @attribute text string @attribute class {spam
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