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  • unpack dependency and repack classes using maven?

    - by u123
    I am trying to unpack a maven artifact A and repack it into a new jar file in the maven project B. Unpacking class files from artifact A into: <my.classes.folder>${project.build.directory}/staging</my.classes.folder> works fine using this: <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-dependency-plugin</artifactId> <executions> <execution> <id>unpack</id> <phase>generate-resources</phase> <goals> <goal>unpack</goal> </goals> <configuration> <artifactItems> <artifactItem> <groupId>com.test</groupId> <artifactId>mvn-sample</artifactId> <version>1.0.0-SNAPSHOT</version> <type>jar</type> <overWrite>true</overWrite> <outputDirectory>${my.classes.folder}</outputDirectory> <includes>**/*.class,**/*.xml</includes> </artifactItem> </artifactItems> </configuration> </execution> </executions> </plugin> In the same pom I now want to generate an additional jar containing the classes just unpacked: <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-jar-plugin</artifactId> <version>2.4</version> <executions> <execution> <phase>package</phase> <goals> <goal>jar</goal> </goals> <configuration> <classesdirectory>${my.classes.folder}</classesdirectory> <classifier>sample</classifier> </configuration> </execution> </executions> </plugin> A new jar is created but it does not contain the classes from the: ${my.classes.folder} its simply a copy of the default project jar. Any ideas? I have tried to follow this guide: http://jkrishnaraotech.blogspot.dk/2011/06/unpack-remove-some-classes-and-repack.html but its not working.

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  • Maven 3 - duplicate declaration of version

    - by Taylor Leese
    I just upgraded to m2eclipse version 0.10 which includes an embedded Maven 3 and I'm now getting the following error when trying to run a build. I've already set Maven-Installations to my Maven 2 installation, but it had no effect. How do I resolve this? [INFO] Scanning for projects... [ERROR] The build could not read 1 project -> [Help 1] [ERROR] The project com.stuff:sutff-web:0.0.1-SNAPSHOT (C:\development\taylor\stuff\pom.xml) has 1 error [ERROR] 'dependencies.dependency.(groupId:artifactId:type:classifier)' must be unique: com.google.appengine:appengine-api-labs:jar -> duplicate declaration of version ${gae.version} [ERROR] [ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch. [ERROR] Re-run Maven using the -X switch to enable full debug logging. [ERROR] [ERROR] For more information about the errors and possible solutions, please read the following articles: [ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException

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  • ClassFormatError when using javaee:javaee-api

    - by Digambar Daund
    This is my pom.xml <?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>dd</groupId> <artifactId>jee6</artifactId> <version>0.0.1-SNAPSHOT</version> </parent> <groupId>dd</groupId> <artifactId>business-tier-impl</artifactId> <name>business-tier-impl</name> <version>0.0.1-SNAPSHOT</version> <packaging>ejb</packaging> <description>business-tier-impl</description> <dependencies> <dependency> <groupId>javax</groupId> <artifactId>javaee-api</artifactId> <version>6.0</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.testng</groupId> <artifactId>testng</artifactId> <version>5.11</version> <scope>test</scope> <classifier>jdk15</classifier> </dependency> <dependency> <groupId>org.apache.openejb</groupId> <artifactId>openejb-core</artifactId> <version>3.1.2</version> <scope>test</scope> </dependency> </dependencies> <build> <plugins> <plugin> <artifactId>maven-compiler-plugin</artifactId> <configuration> <source>1.6</source> <target>1.6</target> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-ejb-plugin</artifactId> <configuration> <ejbVersion>3.1.2</ejbVersion> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-surefire-plugin</artifactId> </plugin> </plugins> </build> </project> Below is the testcase setup methhod: @BeforeClass public void bootContainer() throws Exception { Properties props = new Properties(); props.setProperty(Context.INITIAL_CONTEXT_FACTORY, LocalInitialContextFactory.class.getName()); Context context = new InitialContext(props); service = (HelloService) context.lookup("HelloServiceLocal"); } I get error at line where InitialContext() is created... Apache OpenEJB 3.1 build: 20081009-03:31 http://openejb.apache.org/ INFO - openejb.home = C:\DD\WORKSPACES\jee6\business-tier-impl INFO - openejb.base = C:\DD\WORKSPACES\jee6\business-tier-impl FATAL - OpenEJB has encountered a fatal error and cannot be started: OpenEJB encountered an unexpected error while attempting to instantiate the assembler. java.lang.ClassFormatError: Absent Code attribute in method that is not native or abstract in class file javax/resource/spi/ResourceAdapterInternalException . . . FAILED CONFIGURATION: @BeforeClass bootContainer javax.naming.NamingException: Attempted to load OpenEJB. OpenEJB has encountered a fatal error and cannot be started: OpenEJB encountered an unexpected error while attempting to instantiate the assembler.: Absent Code attribute in method that is not native or abstract in class file javax/resource/spi/ResourceAdapterInternalException [Root exception is org.apache.openejb.OpenEJBException: OpenEJB has encountered a fatal error and cannot be started: OpenEJB encountered an unexpected error while attempting to instantiate the assembler.: Absent Code attribute in method that is not native or abstract in class file javax/resource/spi/ResourceAdapterInternalException] at org.apache.openejb.client.LocalInitialContextFactory.init(LocalInitialContextFactory.java:54) at org.apache.openejb.client.LocalInitialContextFactory.getInitialContext(LocalInitialContextFactory.java:41) at javax.naming.spi.NamingManager.getInitialContext(NamingManager.java:667) at javax.naming.InitialContext.getDefaultInitCtx(InitialContext.java:288) at javax.naming.InitialContext.init(InitialContext.java:223) at javax.naming.InitialContext.<init>(InitialContext.java:197) at dd.jee6.app.HelloServiceTest.bootContainer(HelloServiceTest.java:26) Caused by: org.apache.openejb.OpenEJBException: OpenEJB has encountered a fatal error and cannot be started: OpenEJB encountered an unexpected error while attempting to instantiate the assembler.: Absent Code attribute in method that is not native or abstract in class file javax/resource/spi/ResourceAdapterInternalException at org.apache.openejb.OpenEJB$Instance.<init>(OpenEJB.java:133) at org.apache.openejb.OpenEJB.init(OpenEJB.java:299) at org.apache.openejb.OpenEJB.init(OpenEJB.java:278) at org.apache.openejb.loader.OpenEJBInstance.init(OpenEJBInstance.java:36) at org.apache.openejb.client.LocalInitialContextFactory.init(LocalInitialContextFactory.java:69) at org.apache.openejb.client.LocalInitialContextFactory.init(LocalInitialContextFactory.java:52) ... 28 more Caused by: java.lang.ClassFormatError: Absent Code attribute in method that is not native or abstract in class file javax/resource/spi/ResourceAdapterInternalException at java.lang.ClassLoader.defineClass1(Native Method)

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  • Load application context problem in Maven managed spring-test TestNg

    - by joejax
    I try to setup a project with spring-test using TestNg in Maven. The code is like: @ContextConfiguration(locations={"test-context.xml"}) public class AppTest extends AbstractTestNGSpringContextTests { @Test public void testApp() { assert true; } } A test-context.xml simply defined a bean: <bean id="app" class="org.sonatype.mavenbook.simple.App"/> I got error for Failed to load ApplicationContext when running mvn test from command line, seems it cannot find the test-context.xml file; however, I can get it run correctly inside Eclipse (with TestNg plugin). So, test-context.xml is under src/test/resources/, how do I indicate this in the pom.xml so that 'mvn test' command will work? Thanks, UPDATE: Thanks for the reply. Cannot load context file error was caused by I moved the file arround in different location since I though the classpath was the problem. Now I found the context file seems loaded from the Maven output, but the test is failed: Running TestSuite May 25, 2010 9:55:13 AM org.springframework.beans.factory.xml.XmlBeanDefinitionReader loadBeanDefinitions INFO: Loading XML bean definitions from class path resource [test-context.xml] May 25, 2010 9:55:13 AM org.springframework.context.support.AbstractApplicationContext prepareRefresh INFO: Refreshing org.springframework.context.support.GenericApplicationContext@171bbc9: display name [org.springframework.context.support.GenericApplicationContext@171bbc9]; startup date [Tue May 25 09:55:13 PDT 2010]; root of context hierarchy May 25, 2010 9:55:13 AM org.springframework.context.support.AbstractApplicationContext obtainFreshBeanFactory INFO: Bean factory for application context [org.springframework.context.support.GenericApplicationContext@171bbc9]: org.springframework.beans.factory.support.DefaultListableBeanFactory@1df8b99 May 25, 2010 9:55:13 AM org.springframework.beans.factory.support.DefaultListableBeanFactory preInstantiateSingletons INFO: Pre-instantiating singletons in org.springframework.beans.factory.support.DefaultListableBeanFactory@1df8b99: defining beans [app,org.springframework.context.annotation.internalCommonAnnotationProcessor,org.springframework.context.annotation.internalAutowiredAnnotationProcessor,org.springframework.context.annotation.internalRequiredAnnotationProcessor]; root of factory hierarchy Tests run: 3, Failures: 2, Errors: 0, Skipped: 1, Time elapsed: 0.63 sec If I use spring-test version 3.0.2.RELEASE, the error becomes: org.springframework.test.context.testng.AbstractTestNGSpringContextTests.springTestContextPrepareTestInstance() is depending on nonexistent method null Here is the structure of the project: simple |-- pom.xml `-- src |-- main | `-- java `-- test |-- java `-- resources |-- test-context.xml `-- testng.xml testng.xml: <suite name="Suite" parallel="false"> <test name="Test"> <classes> <class name="org.sonatype.mavenbook.simple.AppTest"/> </classes> </test> </suite> test-context.xml: <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-2.0.xsd" default-lazy-init="true"> <bean id="app" class="org.sonatype.mavenbook.simple.App"/> </beans> In the pom.xml, I add testng, spring, and spring-test artifacts, and plugin: <dependency> <groupId>org.testng</groupId> <artifactId>testng</artifactId> <version>5.1</version> <classifier>jdk15</classifier> <scope>test</scope> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring</artifactId> <version>2.5.6</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-test</artifactId> <version>2.5.6</version> <scope>test</scope> </dependency> <build> <finalName>simple</finalName> <plugins> <plugin> <artifactId>maven-compiler-plugin</artifactId> <configuration> <source>1.6</source> <target>1.6</target> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-surefire-plugin</artifactId> <configuration> <suiteXmlFiles> <suiteXmlFile>src/test/resources/testng.xml</suiteXmlFile> </suiteXmlFiles> </configuration> </plugin> </plugins> Basically, I replaced 'A Simple Maven Project' Junit with TestNg, hope it works.

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  • Text mining with PHP

    - by garyc40
    Hi, I'm doing a project for a college class I'm taking. I'm using PHP to build a simple web app that classify tweets as "positive" (or happy) and "negative" (or sad) based on a set of dictionaries. The algorithm I'm thinking of right now is Naive Bayes classifier or decision tree. However, I can't find any PHP library that helps me do some serious language processing. Python has NLTK (http://www.nltk.org). Is there anything like that for PHP? I'm planning to use WEKA as the back end of the web app (by calling Weka in command line from within PHP), but it doesn't seem that efficient. Do you have any idea what I should use for this project? Or should I just switch to Python? Thanks

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  • Adaboost algorithm and its usage in face detection

    - by Hani
    I am trying to understand Adaboost algorithm but i have some troubles. After reading about Adaboost i realized that it is a classification algorithm(somehow like neural network). But i could not know how the weak classifiers are chosen (i think they are haar-like features for face detection) and how finally the H result which is the final strong classifier can be used. I mean if i found the alpha values and compute the H ,how am i going to benefit from it as a value (one or zero) for new images. Please is there an example describes it in a perfect way? i found the plus and minus example that is found in most adaboost tutorials but i did not know how exactly hi is chosen and how to adopt the same concept on face detection. I read many papers and i had many ideas but until now my ideas are not well arranged. Thanks....

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  • DataMining / Analyzing responses to Multiple Choice Questions in a survey

    - by Shailesh Tainwala
    Hi, I have a set of training data consisting of 20 multiple choice questions (A/B/C/D) answered by a hundred respondents. The answers are purely categorical and cannot be scaled to numerical values. 50 of these respondents were selected for free product trial. The selection process is not known. What interesting knowledge can be mined from this information? The following is a list of what I have come up with so far- A study of percentages (Example - Percentage of people who answered B on Qs.5 and got selected for free product trial) Conditional probabilities (Example - What is the probability that a person will get selected for free product trial given that he answered B on Qs.5) Naive Bayesian classifier (This can be used to predict whether a person will be selected or not for a given set of values for any subset of questions). Can you think of any other interesting analysis or data-mining activities that can be performed? The usual suspects like correlation can be eliminated as the response is not quantifiable/scoreable. Is my approach correct?

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  • springTestContextBeforeTestMethod failed in Maven spring-test

    - by joejax
    I try to setup a project with spring-test using TestNg in Maven. The code is like: @ContextConfiguration(locations={"test-context.xml"}) public class AppTest extends AbstractTestNGSpringContextTests { @Test public void testApp() { assert true; } } A test-context.xml simply defined a bean: <bean id="app" class="org.sonatype.mavenbook.simple.App"/> I got error for Failed to load ApplicationContext when running mvn test from command line, seems it cannot find the test-context.xml file; however, I can get it run correctly inside Eclipse (with TestNg plugin). So, test-context.xml is under src/test/resources/, how do I indicate this in the pom.xml so that 'mvn test' command will work? Thanks, UPDATE: Thanks for the reply. Cannot load context file error was caused by I moved the file arround in different location since I though the classpath was the problem. Now I found the context file seems loaded from the Maven output, but the test is failed: Running TestSuite May 25, 2010 9:55:13 AM org.springframework.beans.factory.xml.XmlBeanDefinitionReader loadBeanDefinitions INFO: Loading XML bean definitions from class path resource [test-context.xml] May 25, 2010 9:55:13 AM org.springframework.context.support.AbstractApplicationContext prepareRefresh INFO: Refreshing org.springframework.context.support.GenericApplicationContext@171bbc9: display name [org.springframework.context.support.GenericApplicationContext@171bbc9]; startup date [Tue May 25 09:55:13 PDT 2010]; root of context hierarchy May 25, 2010 9:55:13 AM org.springframework.context.support.AbstractApplicationContext obtainFreshBeanFactory INFO: Bean factory for application context [org.springframework.context.support.GenericApplicationContext@171bbc9]: org.springframework.beans.factory.support.DefaultListableBeanFactory@1df8b99 May 25, 2010 9:55:13 AM org.springframework.beans.factory.support.DefaultListableBeanFactory preInstantiateSingletons INFO: Pre-instantiating singletons in org.springframework.beans.factory.support.DefaultListableBeanFactory@1df8b99: defining beans [app,org.springframework.context.annotation.internalCommonAnnotationProcessor,org.springframework.context.annotation.internalAutowiredAnnotationProcessor,org.springframework.context.annotation.internalRequiredAnnotationProcessor]; root of factory hierarchy Tests run: 3, Failures: 2, Errors: 0, Skipped: 1, Time elapsed: 0.63 sec <<< FAILURE! Results : Failed tests: springTestContextBeforeTestMethod(org.sonatype.mavenbook.simple.AppTest) springTestContextAfterTestMethod(org.sonatype.mavenbook.simple.AppTest) Tests run: 3, Failures: 2, Errors: 0, Skipped: 1 If I use spring-test version 3.0.2.RELEASE, the error becomes: org.springframework.test.context.testng.AbstractTestNGSpringContextTests.springTestContextPrepareTestInstance() is depending on nonexistent method null Here is the structure of the project: simple |-- pom.xml `-- src |-- main | `-- java `-- test |-- java `-- resources |-- test-context.xml `-- testng.xml testng.xml: <suite name="Suite" parallel="false"> <test name="Test"> <classes> <class name="org.sonatype.mavenbook.simple.AppTest"/> </classes> </test> </suite> test-context.xml: <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-2.0.xsd" default-lazy-init="true"> <bean id="app" class="org.sonatype.mavenbook.simple.App"/> </beans> In the pom.xml, I add testng, spring, and spring-test artifacts, and plugin: <dependency> <groupId>org.testng</groupId> <artifactId>testng</artifactId> <version>5.1</version> <classifier>jdk15</classifier> <scope>test</scope> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring</artifactId> <version>2.5.6</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-test</artifactId> <version>2.5.6</version> <scope>test</scope> </dependency> <build> <finalName>simple</finalName> <plugins> <plugin> <artifactId>maven-compiler-plugin</artifactId> <configuration> <source>1.6</source> <target>1.6</target> </configuration> </plugin> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-surefire-plugin</artifactId> <configuration> <suiteXmlFiles> <suiteXmlFile>src/test/resources/testng.xml</suiteXmlFile> </suiteXmlFiles> </configuration> </plugin> </plugins> Basically, I replaced 'A Simple Maven Project' Junit with TestNg, hope it works. UPDATE: I think I got the problem (still don't know why) - Whenever I extends AbstractTestNGSpringContextTests or AbstractTransactionalTestNGSpringContextTests, the test will failed with this error: Failed tests: springTestContextBeforeTestMethod(org.sonatype.mavenbook.simple.AppTest) springTestContextAfterTestMethod(org.sonatype.mavenbook.simple.AppTest) So, eventually the error went away when I override the two methods. I don't think this is the right way, didn't find much info from spring-test doc. If you know spring test framework, please shred some light on this.

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  • Implementing a linear, binary SVM (support vector machine)

    - by static_rtti
    I want to implement a simple SVM classifier, in the case of high-dimensional binary data (text), for which I think a simple linear SVM is best. The reason for implementing it myself is basically that I want to learn how it works, so using a library is not what I want. The problem is that most tutorials go up to an equation that can be solved as a "quadratic problem", but they never show an actual algorithm! So could you point me either to a very simple implementation I could study, or (better) to a tutorial that goes all the way to the implementation details? Thanks a lot!

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  • Pyparsing CSV string with random quotes

    - by gtfx
    Hey, I have a string like the following: <118date=2010-05-09,time=16:41:27,device_id=FE-2KA3F09000049,log_id=0400147717,log_part=00,type=statistics,subtype=n/a,pri=information,session_id=o49CedRc021772,from="[email protected]",mailer="mta",client_name="example.org,[194.177.17.24]",resolved=OK,to="[email protected]",direction="in",message_length=6832079,virus="",disposition="Accept",classifier="Not,Spam",subject="=?windows-1255?B?Rlc6IEZ3OiDg5fDp5fog+fno5fog7Pf46eHp7S3u4+Tp7SE=?=" I tried using CSV module and it didn't fit, cause i haven't found a way to ignore what's quoted. Pyparsing looked like a better answer but i haven't found a way to declare all the grammars. Currently, i am using my old Perl script to parse it, but i want this written in Python. if you need my Perl snippet i will be glad to provide it. Any help is appreciated.

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  • Algorithm to classify a list of products?

    - by Martin
    I have a list representing products which are more or less the same. For instance, in the list below, they are all Seagate hard drives. Seagate Hard Drive 500Go Seagate Hard Drive 120Go for laptop Seagate Barracuda 7200.12 ST3500418AS 500GB 7200 RPM SATA 3.0Gb/s Hard Drive New and shinny 500Go hard drive from Seagate Seagate Barracuda 7200.12 Seagate FreeAgent Desk 500GB External Hard Drive Silver 7200RPM USB2.0 Retail For a human being, the hard drives 3 and 5 are the same. We could go a little bit further and suppose that the products 1, 3, 4 and 5 are the same and put in other categories the product 2 and 6. We have a huge list of products that I would like to classify. Does anybody have an idea of what would be the best algorithm to do such thing. Any suggestions? I though of a Bayesian classifier but I am not sure if it is the best choice. Any help would be appreciated! Thanks.

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  • Extracting Information from Images

    - by Khorkrak
    What are some fast and somewhat reliable ways to extract information about images? I've been tinkering with openCV and this seems so far to be the best route plus it has Python bindings. So to be more specific I'd like to determine what I can about what's in an image. So for example the haar face detection and full body detection classifiers are great - now I can tell that most likely there are faces and / or people in the image as well as about how many. okay - what else - how about whether there are any buildings and if so what do they seem to be - huts, office buildings etc? Is there sky visible, grass, trees and so forth. From what I've read about training classifiers to detect objects, it seems like a rather laborious process 10,000 or so wrong images and 5,000 or so correct samples to train a classifier. I'm hoping that there are some decent ones around already instead of having to do this all myself for a bunch of different objects - or is there some other way to go about this sort of thing?

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  • choose the best class if 2 class have same P (c|d), naive bayes

    - by ryandi
    Hello I have some question about naive bayes classifier . In my project I have to classify a text into a class from 4 available class. In naive bayes we have formula like cmap=argmax.P(d|c).P(c) I have standarize the amount of training document of each class, so I got a same P(c) value for each class (0.25). Here's my question: What if a testing document token doesn't have any token which belong to any of those 4 class(in document training)? Resulted to all of the class have same value of P(d|c).P(c). Which class should i pick? What if the token exist, and 2 class or more have same value of P(d|c).P(c) what should I do? Thank you..

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  • Distance between hyperplanes

    - by michael dillard
    I'm trying to teach myself some machine learning, and have been using the MNIST database (http://yann.lecun.com/exdb/mnist/) do so. The author of that site wrote a paper in '98 on all different kinds of handwriting recognition techniques, available at http://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf. The 10th method mentioned is a "Tangent Distance Classifier". The idea being that if you place each image in a (NxM)-dimensional vector space, you can compute the distance between two images as the distance between the hyperplanes formed by each where the hyperplane is given by taking the point, and rotating the image, rescaling the image, translating the image, etc. I can't figure out enough to fill in the missing details. I understand that most of these are indeed linear operators, so how does one use that fact to then create the hyperplane? And once we have a hyperplane, how do we take its distance with other hyperplanes?

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  • Inter-rater agreement (Fleiss' Kappa, Krippendorff's Alpha etc) Java API?

    - by adam
    I am working on building a Question Classification/Answering corpus as a part of my masters thesis. I'm looking at evaluating my expected answer type taxonomy with respect to inter-rater agreement/reliability, and I was wondering: Does anybody know of any decent (preferably free) Java API(s) that can do this? I'm reasonably certain all I need is Fleiss' Kappa and Krippendorff's Alpha at this point. Weka provides a kappa statistic in it's evaluation package, but I think it can only evaluate a classifier and I'm not at that stage yet (because I'm still building the data set and classes). Thanks.

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  • Python finding index in a array

    - by NIH
    I am trying to see if a company from a list of companies is in a line in a file. If it is I utilize the index of that company to increment a variable in another array. The following is my python code. I keep getting the following error: AttributeError: 'set' object has no attribute 'index'. I cannot figure out what is going wrong and think the error is the line that is surrounded by **. companies={'white house black market', 'macy','nordstrom','filene','walmart'} positives=[0 for x in xrange(len(companies))] negatives=[0 for x in xrange(len(companies))] for line in f: for company in companies: if company in line.lower(): words=tokenize.word_tokenize(line) bag=bag_of_words(words) classif=classifier.classify(bag) if classif=='pos': **indice =companies.index(company)** positives[indice]+=1 elif classif=='neg': **indice =companies.index(company)** negatives[indice]+=1

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  • Sentiment analysis for twitter in python

    - by Ran
    I'm looking for an open source implementation, preferably in python, of Textual Sentiment Analysis (http://en.wikipedia.org/wiki/Sentiment_analysis). Is anyone familiar with such open source implementation I can use? I'm writing an application that searches twitter for some search term, say "youtube", and counts "happy" tweets vs. "sad" tweets. I'm using Google's appengine, so it's in python. I'd like to be able to classify the returned search results from twitter and I'd like to do that in python. I haven't been able to find such sentiment analyzer so far, specifically not in python. Are you familiar with such open source implementation I can use? Preferably this is already in python, but if not, hopefully I can translate it to python. Note, the texts I'm analyzing are VERY short, they are tweets. So ideally, this classifier is optimized for such short texts. BTW, twitter does support the ":)" and ":(" operators in search, which aim to do just this, but unfortunately, the classification provided by them isn't that great, so I figured I might give this a try myself. Thanks! BTW, an early demo is here and the code I have so far is here and I'd love to opensource it with any interested developer.

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  • Calculating Nearest Match to Mean/Stddev Pair With LibSVM

    - by Chris S
    I'm new to SVMs, and I'm trying to use the Python interface to libsvm to classify a sample containing a mean and stddev. However, I'm getting nonsensical results. Is this task inappropriate for SVMs or is there an error in my use of libsvm? Below is the simple Python script I'm using to test: #!/usr/bin/env python # Simple classifier test. # Adapted from the svm_test.py file included in the standard libsvm distribution. from collections import defaultdict from svm import * # Define our sparse data formatted training and testing sets. labels = [1,2,3,4] train = [ # key: 0=mean, 1=stddev {0:2.5,1:3.5}, {0:5,1:1.2}, {0:7,1:3.3}, {0:10.3,1:0.3}, ] problem = svm_problem(labels, train) test = [ ({0:3, 1:3.11},1), ({0:7.3,1:3.1},3), ({0:7,1:3.3},3), ({0:9.8,1:0.5},4), ] # Test classifiers. kernels = [LINEAR, POLY, RBF] kname = ['linear','polynomial','rbf'] correct = defaultdict(int) for kn,kt in zip(kname,kernels): print kt param = svm_parameter(kernel_type = kt, C=10, probability = 1) model = svm_model(problem, param) for test_sample,correct_label in test: pred_label, pred_probability = model.predict_probability(test_sample) correct[kn] += pred_label == correct_label # Show results. print '-'*80 print 'Accuracy:' for kn,correct_count in correct.iteritems(): print '\t',kn, '%.6f (%i of %i)' % (correct_count/float(len(test)), correct_count, len(test)) The domain seems fairly simple. I'd expect that if it's trained to know a mean of 2.5 means label 1, then when it sees a mean of 2.4, it should return label 1 as the most likely classification. However, each kernel has an accuracy of 0%. Why is this? On a side note, is there a way to hide all the verbose training output dumped by libsvm in the terminal? I've searched libsvm's docs and code, but I can't find any way to turn this off.

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  • PCA extended face recognition

    - by cMinor
    The state of the art says that we can use PCA to perform face recognition. like this, this or this I am working with a project that involves training a classifier to detect a person who is wearing glasess or hats or even a mustache. The purpose of doing this is to detect when a person that has robbed a bank, store, or have commeted some sort of crime(s) (we have their image in a database), enters a certain place ( historically we know these guys have robbed, so we should take care to avoid problems). We came first to have a distributed database with all images of criminals, then I thought to have a layer of them clasifying these criminals using accesories like hats, mustache or anything that hides their face etc... Then, to apply that knowledge to detect when a particular or a suspect person enters a comercial place. ( In practice when someone is going to rob not all the times they are using an accesorie...) What do you think about this idea of doing PCA to first detect principal components of the face and then the components of an accesory. I was thinking that maybe a probabilistic approach is better so we can compute the probability the criminal is the person that entered a place and call the respective authorities.

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  • Publishing artifacts with sources on archiva

    - by Palimondo
    At work I'm dipping my toes in managing project dependencies with maven. We use Apache Archiva (1.2.1) as a local repository and proxy. I'm adding artifact for open source project, that is not published on any public repository. I've learned that to publish the sources I should use the Classifier field on Upload artifact page. The sources are then listed alongside the jar and pom when I browse the repository. But when I update my maven dependencies I get only the jar and pom from the repository. I noticed that sources are also missing when the archiva proxies for me the downloads from other public repositories. I didn't find any configuration options in Archiva's admin pages to serve the sources... What am I missing? Update: I was missing the fact that artifact sources have to be downloaded manually. I.e. the maven client has to request them, which is controlled by command line option -DdownloadSources=true. Maven Integration for Eclipse has a preference setting to always download them as described in Resolving artifact sources. Archiva then serves the sources for local artifacts or proxies the request to remote repositories and caches the sources for future requests.

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  • UnknownHostException while redirecting queries to google and getting results in JSon object

    - by shilpa
    Loading classifier from D:\PROJECT\classifiers\NERDemo\classifiers\ner-eng-ie.crf-3-all2008.ser.gz ... done [2.0 sec]. Original Query was riot in India. Parsing Queries and expanding tokens from the Ontologies.. {locations=[India], events=[riot]} Search query is null Something went wrong... java.net.UnknownHostException: ajax.googleapis.com at java.net.PlainSocketImpl.connect(Unknown Source) at java.net.SocksSocketImpl.connect(Unknown Source) at java.net.Socket.connect(Unknown Source) at java.net.Socket.connect(Unknown Source) at sun.net.NetworkClient.doConnect(Unknown Source) at sun.net.www.http.HttpClient.openServer(Unknown Source) at sun.net.www.http.HttpClient.openServer(Unknown Source) at sun.net.www.http.HttpClient.<init>(Unknown Source) at sun.net.www.http.HttpClient.New(Unknown Source) at sun.net.www.http.HttpClient.New(Unknown Source) at sun.net.www.protocol.http.HttpURLConnection.getNewHttpClient(Unknown Source) at sun.net.www.protocol.http.HttpURLConnection.plainConnect(Unknown Source) at sun.net.www.protocol.http.HttpURLConnection.connect(Unknown Source) at sun.net.www.protocol.http.HttpURLConnection.getInputStream(Unknown Source) at org.girs2.SearchHandler.makeQuery(SearchHandler.java:35) at org.girs2.GIRS.search(GIRS.java:37) at org.girs2.GIRS.main(GIRS.java:62) Exception in thread "main" java.lang.NullPointerException at org.girs2.GIRS.search(GIRS.java:44) at org.girs2.GIRS.main(GIRS.java:62)

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  • Calculate posterior distribution of unknown mis-classification with PRTools in MATLAB

    - by Samuel Lampa
    I'm using the PRTools MATLAB library to train some classifiers, generating test data and testing the classifiers. I have the following details: N: Total # of test examples k: # of mis-classification for each classifier and class I want to do: Calculate and plot Bayesian posterior distributions of the unknown probabilities of mis-classification (denoted q), that is, as probability density functions over q itself (so, P(q) will be plotted over q, from 0 to 1). I have that (math formulae, not matlab code!): P(q|k,N) = Posterior * Prior / Normalization constant = P(k|q,N) * P(q|N) / P(k|N) The prior is set to 1, so I only need to calculate the posterior and normalization constant. I know that the posterior can be expressed as (where B(N,k) is the binomial coefficient): P(k|q,N) = B(N,k) * q^k * (1-q)^(N-k) ... so the Normalization constant is simply an integral of the posterior above, from 0 to 1: P(k|N) = B(N,k) * integralFromZeroToOne( q^k * (1-q)^(N-k) ) (The Binomial coefficient ( B(N,k) ) can be omitted thoughappears in both the posterior and normalization constant, so it can be omitted.) Now, I've heard that the integral for the normalization constant should be able to be calculated as a series ... something like: k!(N-k)! / (N+1)! Is that correct? (I have some lecture notes from with this series, but can't figure out if it is for the normalization constant integral, or for the posterior distribution of mis-classification (q)) Also, hints are welcome as how to practically calculate this? (factorials are easily creating truncation errors right?) ... AND, how to practically calculate the final plot (the posterior distribution over q, from 0 to 1).

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  • Naive Bayesian classification (spam filtering) - Doubt in one calculation? Which one is right? Plz c

    - by Microkernel
    Hi guys, I am implementing Naive Bayesian classifier for spam filtering. I have doubt on some calculation. Please clarify me what to do. Here is my question. In this method, you have to calculate P(S|W) - Probability that Message is spam given word W occurs in it. P(W|S) - Probability that word W occurs in a spam message. P(W|H) - Probability that word W occurs in a Ham message. So to calculate P(W|S), should I do (1) (Number of times W occuring in spam)/(total number of times W occurs in all the messages) OR (2) (Number of times word W occurs in Spam)/(Total number of words in the spam message) So, to calculate P(W|S), should I do (1) or (2)? (I thought it to be (2), but I am not sure, so plz clarify me) I am refering http://en.wikipedia.org/wiki/Bayesian_spam_filtering for the info by the way. I got to complete the implementation by this weekend :( Thanks and regards, MicroKernel :) @sth: Hmm... Shouldn't repeated occurrence of word 'W' increase a message's spam score? In the your approach it wouldn't, right?. Lets take a scenario and discuss... Lets say, we have 100 training messages, out of which 50 are spam and 50 are Ham. and say word_count of each message = 100. And lets say, in spam messages word W occurs 5 times in each message and word W occurs 1 time in Ham message. So total number of times W occuring in all the spam message = 5*50 = 250 times. And total number of times W occuring in all Ham messages = 1*50 = 50 times. Total occurance of W in all of the training messages = (250+50) = 300 times. So, in this scenario, how do u calculate P(W|S) and P(W|H) ? Naturally we should expect, P(W|S) P(W|H)??? right. Please share your thought...

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  • Questions about the Backpropogation Algorithm

    - by Colemangrill
    I have a few questions concerning backpropogation. I'm trying to learn the fundamentals behind neural network theory and wanted to start small, building a simple XOR classifier. I've read a lot of articles and skimmed multiple textbooks - but I can't seem to teach this thing the pattern for XOR. Firstly, I am unclear about the learning model for backpropogation. Here is some pseudo-code to represent how I am trying to train the network. [Lets assume my network is setup properly (ie: multiple inputs connect to a hidden layer connect to an output layer and all wired up properly)]. SET guess = getNetworkOutput() // Note this is using a sigmoid activation function. SET error = desiredOutput - guess SET delta = learningConstant * error * sigmoidDerivative(guess) For Each Node in inputNodes For Each Weight in inputNodes[n] inputNodes[n].weight[j] += delta; // At this point, I am assuming the first layer has been trained. // Then I recurse a similar function over the hidden layer and output layer. // The prime difference being that it further divi's up the adjustment delta. I realize this is probably not enough to go off of, and I will gladly expound on any part of my implementation. Using the above algorithm, my neural network does get trained, kind of. But not properly. The output is always XOR 1 1 [smallest number] XOR 0 0 [largest number] XOR 1 0 [medium number] XOR 0 1 [medium number] I can never train the [1,1] [0,0] to be the same value. If you have any suggestions, additional resources, articles, blogs, etc for me to look at I am very interested in learning more about this topic. Thank you for your assistance, I appreciate it greatly!

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  • Android - Adding external library to project

    - by mmontalbo
    Hi, I am having a lot of trouble adding the WEKA library to a project I am working on. I have followed several tutorials that explain how to do this including the Android Developers guide: http://developer.android.com/guide/appendix/faq/commontasks.html#addexternallibrary and several of the postings on SO. I have created a folder in my project with the weka.jar file, created a new library (adding the weka.jar file to the library) and included this library in my build path. I have also added the library under the "Order and Export" tab in the project properties. I have also tried importing the jar file so that the actual contents of the jar are extracted into a directory in my project. The end result of all of this is that my project is able to build correctly and without error, but when it comes time to run my code on the emulator I get the following exception: 04-10 22:52:21.051: ERROR/dalvikvm(582): Could not find class 'weka.classifiers.trees.J48', referenced from method edu.usc.student.composure.classifier.GaitClassifierImpl. with J48 being the class I reference in my code. Does anyone have any additional suggestions that I may have overlooked? Thanks!

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