But since 0.5 is released, we can't change the source any more, I must go with the latest trunk, which I can't build in my environment, can you help with trunk building problem also please.
Regards, Xiaobo Gu > -----Original Message----- > From: Sean Owen [mailto:sro...@gmail.com] > Sent: Thursday, June 30, 2011 9:54 PM > To: dev@mahout.apache.org > Subject: Re: [jira] [Updated] (MAHOUT-696) Command line program for > AdaptiveLogiscticRegression > > I think this is a bug since this class is read as a Writable, which > means it needs a no-arg constructor, but it has none. I will just add > one now. > > Sean > > On Thu, Jun 30, 2011 at 2:17 PM, XiaoboGu <guxiaobo1...@gmail.com> wrote: > > The latest mahout-696.path can work with mahout-trunk rev1104229, which is > > my > development revision, but when patched with 0.5 release, the following error > occur when run > validateAdaptiveLogistic > > > > > > Exception in thread "main" java.io.IOException: Can't create object > > at > org.apache.mahout.classifier.sgd.PolymorphicWritable.read(PolymorphicWritable.java:45) > > at > org.apache.mahout.classifier.sgd.OnlineLogisticRegression.readFields(OnlineLogisticRegre > ssion.java:162) > > at > org.apache.mahout.classifier.sgd.CrossFoldLearner.readFields(CrossFoldLearner.java:317) > > at > org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression$Wrapper.readFields(Adaptive > LogisticRegression.java:435) > > at > org.apache.mahout.classifier.sgd.PolymorphicWritable.read(PolymorphicWritable.java:51) > > at org.apache.mahout.ep.State.readFields(State.java:297) > > at > org.apache.mahout.classifier.sgd.PolymorphicWritable.read(PolymorphicWritable.java:51) > > at > org.apache.mahout.ep.EvolutionaryProcess.readFields(EvolutionaryProcess.java:222) > > at > org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.readFields(AdaptiveLogisticR > egression.java:539) > > at > org.apache.mahout.classifier.sgd.AdaptiveLogisticModelParameters.readFields(AdaptiveLo > gisticModelParameters.java:173) > > at > org.apache.mahout.classifier.sgd.AdaptiveLogisticModelParameters.loadFromStream(Adap > tiveLogisticModelParameters.java:179) > > at > org.apache.mahout.classifier.sgd.AdaptiveLogisticModelParameters.loadFromFile(Adaptive > LogisticModelParameters.java:186) > > at > org.apache.mahout.classifier.sgd.ValidateAdaptiveLogistic.main(ValidateAdaptiveLogistic.j > ava:70) > > Caused by: java.lang.InstantiationException: > org.apache.mahout.classifier.sgd.ElasticBandPrior > > at java.lang.Class.newInstance0(Class.java:340) > > at java.lang.Class.newInstance(Class.java:308) > > at > org.apache.mahout.classifier.sgd.PolymorphicWritable.read(PolymorphicWritable.java:43) > > ... 12 more > > > > > > > > > >> -----Original Message----- > >> From: Lance Norskog [mailto:goks...@gmail.com] > >> Sent: Thursday, June 30, 2011 11:26 AM > >> To: dev@mahout.apache.org > >> Subject: Re: [jira] [Updated] (MAHOUT-696) Command line program for > >> AdaptiveLogiscticRegression > >> > >> Thanks for this project, Xiaobo! I look forward to playing with it. > >> > >> Lance > >> > >> On Wed, Jun 29, 2011 at 8:21 PM, XiaoboGu (JIRA) <j...@apache.org> wrote: > >> > > >> > [ > >> > https://issues.apache.org/jira/browse/MAHOUT-696?page=com.atlassian.jira.plu > gin > >> .system.issuetabpanels:all-tabpanel ] > >> > > >> > XiaoboGu updated MAHOUT-696: > >> > ---------------------------- > >> > > >> > Attachment: MAHOUT-696.patch > >> > > >> > This version has passed the following testes: > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --showperf > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 > >> > > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior L1 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior L2 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior up > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior tp > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior ebp > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior tp --prioroption 2 > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior ebp --prioroption 2 > >> > > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior L1 --auc global > >> > mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 > >> > --target color > >> --categories 2 --predictors x y --types numeric --threads 8 --passes 1000 > >> --showperf > >> --features 100 --skipperfnum 399 --prior L1 --auc grouped > >> > > >> > mahout validateAdaptiveLogistic --input donut-test.csv --model > >> > d:\\model1 --auc > >> --confusion --scores > >> > > >> > mahout runAdaptiveLogistic --input donut-test.csv --model d:\\model1 > >> > --output > >> d:\\scores.txt --idcolumn c > >> > mahout runAdaptiveLogistic --input donut-test.csv --model d:\\model1 > >> > --output > >> d:\\scores1.txt --idcolumn c --maxscoreonly > >> > > >> > > >> > > >> >> Command line program for AdaptiveLogiscticRegression > >> >> ---------------------------------------------------- > >> >> > >> >> Key: MAHOUT-696 > >> >> URL: https://issues.apache.org/jira/browse/MAHOUT-696 > >> >> Project: Mahout > >> >> Issue Type: Improvement > >> >> Components: Classification > >> >> Affects Versions: 0.5 > >> >> Reporter: XiaoboGu > >> >> Assignee: Ted Dunning > >> >> Fix For: 0.6 > >> >> > >> >> Attachments: MAHOUT-696.patch, MAHOUT-696.patch, > MAHOUT-696.patch, > >> MAHOUT-696.patch, MAHOUT-696.patch, mahout-696-r1.patch, > mahout-696-r2.patch, > >> mahout-696-r3.patch, mahout-696-r4.patch, mahout-696-r5.patch > >> >> > >> >> > >> >> Suggested by Ted, I'll try to write a command line program for > >> AdaptiveLogicticRegression, but as I am not familir with the algorithm, > >> I'll try to write a > >> prototype for the program from a Java developer's perspactive, hope anyone > >> else will help > >> with the details of the algorithm. > >> > > >> > -- > >> > This message is automatically generated by JIRA. > >> > For more information on JIRA, see: http://www.atlassian.com/software/jira > >> > > >> > > >> > > >> > >> > >> > >> -- > >> Lance Norskog > >> goks...@gmail.com > > > >
