Add support for the `isofor` package

[jwveld]

When trying to convert an Iforest model I get the following errors.

nov 30, 2017 3:06:55 PM org.jpmml.rexp.Main run INFO: Parsing RDS.. nov 30, 2017 3:06:56 PM org.jpmml.rexp.Main run INFO: Parsed RDS in 332 ms. nov 30, 2017 3:06:56 PM org.jpmml.rexp.Main run INFO: Initializing default Converter nov 30, 2017 3:06:56 PM org.jpmml.rexp.Main run INFO: Initialized org.jpmml.rexp.IForestConverter nov 30, 2017 3:06:56 PM org.jpmml.rexp.Main run INFO: Converting.. nov 30, 2017 3:06:56 PM org.jpmml.rexp.Main run SEVERE: Failed to convert java.lang.IllegalArgumentException: xcols at org.jpmml.rexp.RVector.getValue(RVector.java:104) at org.jpmml.rexp.RVector.getValue(RVector.java:80) at org.jpmml.rexp.IForestConverter.encodeSchema(IForestConverter.java:59) at org.jpmml.rexp.ModelConverter.encodePMML(ModelConverter.java:74) at org.jpmml.rexp.ModelConverter.encodePMML(ModelConverter.java:70) at org.jpmml.rexp.Main.run(Main.java:149) at org.jpmml.rexp.Main.main(Main.java:97)

Exception in thread "main" java.lang.IllegalArgumentException: xcols at org.jpmml.rexp.RVector.getValue(RVector.java:104) at org.jpmml.rexp.RVector.getValue(RVector.java:80) at org.jpmml.rexp.IForestConverter.encodeSchema(IForestConverter.java:59) at org.jpmml.rexp.ModelConverter.encodePMML(ModelConverter.java:74) at org.jpmml.rexp.ModelConverter.encodePMML(ModelConverter.java:70) at org.jpmml.rexp.Main.run(Main.java:149) at org.jpmml.rexp.Main.main(Main.java:97) Error in .convert(tempfile, file, converter, converter_classpath, verbose) : 1 In addition: Warning message: running command '"java" -cp "J:/R_werk/R/library/r2pmml/java/guava-20.0.jar;J:/R_werk/R/library/r2pmml/java/istack-commons-runtime-3.0.5.jar;J:/R_werk/R/library/r2pmml/java/jaxb-core-2.3.0.jar;J:/R_werk/R/library/r2pmml/java/jaxb-runtime-2.3.0.jar;J:/R_werk/R/library/r2pmml/java/jcommander-1.48.jar;J:/R_werk/R/library/r2pmml/java/jpmml-converter-1.2.6.jar;J:/R_werk/R/library/r2pmml/java/jpmml-r-1.2.20.jar;J:/R_werk/R/library/r2pmml/java/jpmml-xgboost-1.2.3.jar;J:/R_werk/R/library/r2pmml/java/pmml-agent-1.3.8.jar;J:/R_werk/R/library/r2pmml/java/pmml-model-1.3.8.jar;J:/R_werk/R/library/r2pmml/java/pmml-model-metro-1.3.8.jar;J:/R_werk/R/library/r2pmml/java/pmml-schema-1.3.8.jar;J:/R_werk/R/library/r2pmml/java/slf4j-api-1.7.25.jar;J:/R_werk/R/library/r2pmml/java/slf4j-jdk14-1.7.25.jar" org.jpmml.rexp.Main --rds-input "C:\Users\ADMINV~2\AppData\Local\Temp\3\RtmpKAvfFn\r2pmml-3ee2c512c6347.rds" --pmml-output "text.pmml"' had status 1

[vruusmann]

Reproducible example?

java.lang.IllegalArgumentException: xcols at org.jpmml.rexp.RVector.getValue(RVector.java:104)

Your iForest model object does not have the xcols element. I've seen the same (or very similar) exception before, and IIRC, the cause was that the training dataset contained non-numeric features.

Since the iForest model object is incomplete/invalid, you shouldn't be able to use it for prediction in R either. Can you verify, the IsolationForest::AnomalyScore function should fail with an error?

[jwveld]

Hi Villu,

Thanks for your reply I’m using the isofor package in R. And it scores nicely.

IsolationForest::AnomalyScore = not a command the package knows.

Jan

Package: isofor Type: Package Title: Isolation Forest Anomaly Detection Version: 0.1.3 Authors@R: c( person("Eric", "Graves", email = "gravcon@gmail.com", role = "cre"), person("Ignat", "Drozdov", email = "idrozdov@beringresearch.com", role = "aut")) Description: One efficient way of performing outlier detection in high-dimensional datasets is to use random forests. The isofor ‘isolates’ observations by randomly selecting a feature and then randomly selecting a split

Op 1 dec. 2017, om 05:53 heeft Villu Ruusmann notifications@github.com het volgende geschreven:

Reproducible example?

java.lang.IllegalArgumentException: xcols at org.jpmml.rexp.RVector.getValue(RVector.java:104)

Your iForest model object does not have the xcols element. I've seen the same (or very similar) exception before, and IIRC, the cause was that the training dataset contained non-numeric features.

Since the iForest model object is incomplete/invalid, you shouldn't be able to use it for prediction in R either. Can you verify, the IsolationForest::AnomalyScore function should fail with an error?

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[vruusmann]

I’m using the isofor package in R. And it scores nicely.

The r2pmml package only knows about isolation forest (IF) models that have been trained using the IsolationForest package: https://r-forge.r-project.org/R/?group_id=479

You're using an alternative IF implementation, and it is no wonder that r2pmml can't understand what's going on (the model type is determined based on its R class name, and looks like both IF implementations are producing iForest classes then?).

For your information, the full list of supported R packages/model types is listed in the README file of the JPMML-R library: https://github.com/jpmml/jpmml-r#features

[vruusmann]

Will try to look into functional differences between IsolationForest and isofor packages mid-December, when I'm back from my very-very long business trip.

[jwveld]

Hello Villu,

Thank you.. I will try the IsolationForest implementation.

And curious about you findings concerning isofor.

Jan

Op 1 dec. 2017, om 14:59 heeft Villu Ruusmann notifications@github.com het volgende geschreven:

Will try to look into functional differences between IsolationForest and isofor packages mid-December, when I'm back from my very-very long business trip.

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