GLM: when run with offset get java.lang.AssertionError

Description

cc = h2o.importFile(object=h,path="/Users/nidhimehta/Desktop/cancar_logIn.csv",key = "cc")
cc$Merit = as.factor(cc$Merit)
cc$Class = as.factor(cc$Class)
myX =c("Merit","Class")
myY = "Claims"
hh = h2o.glm(x=myX,y=myY,data=cc,offset="logInsured",family="poisson",link="log",lambda=0)

 

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Polling fails:
<simpleError in .h2o.__poll(client, job_key): Got exception 'class java.lang.AssertionError', with msg 'null'
java.lang.AssertionError
at hex.glm.GLM2$2$1.callback(GLM2.java:1216)
at hex.glm.GLM2$2$1.callback(GLM2.java:1203)
at water.H2O$H2OCallback.onCompletion(H2O.java:680)
at jsr166y.CountedCompleter.tryComplete(CountedCompleter.java:386)
at water.MRTask2.compute2(MRTask2.java:426)
at water.H2O$H2OCountedCompleter.compute(H2O.java:656)
at jsr166y.CountedCompleter.exec(CountedCompleter.java:429)
at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974)
at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)

from R get-
cc= as.data.frame.H2OParsedData(cc)
cc$Merit = as.factor(cc$Merit)
> cc$Class = as.factor(cc$Class)
> gg = glm(formula=formula,family=poisson,data=cc,offset=logInsured)
> summary(gg)

Call:
glm(formula = formula, family = poisson, data = cc, offset = logInsured)

Deviance Residuals:
Min 1Q Median 3Q Max
-10.793 -3.008 -1.576 2.427 11.625

Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.035736 0.004311 -472.19 <2e-16 ***
Merit1 -0.137759 0.007172 -19.21 <2e-16 ***
Merit2 -0.220680 0.007997 -27.59 <2e-16 ***
Merit3 -0.492951 0.004502 -109.49 <2e-16 ***
Class2 0.299830 0.007258 41.31 <2e-16 ***
Class3 0.469055 0.005039 93.08 <2e-16 ***
Class4 0.525855 0.005365 98.02 <2e-16 ***
Class5 0.215550 0.010735 20.08 <2e-16 ***

Signif. codes: 0 ‘**’ 0.001 ‘*’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for poisson family taken to be 1)

Null deviance: 33854.16 on 19 degrees of freedom
Residual deviance: 579.52 on 12 degrees of freedom
AIC: 805.93

Number of Fisher Scoring iterations: 3

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Assignee

Tomas Nykodym

Reporter

Nidhi Mehta

CustomerVisible

No