Basic Usage Parameters
By: Tushar Khot, Sriraam Natarajan
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Note that this is for learning an RDN. The basic version boosts a single conditional relational probability distribution.
java -cp BoostSRL.jar edu.wisc.cs.Boosting.RDN.RunBoostedRDN [Args]
java -jar BoostSRL.jar [Args]
-
-l
: enable training (learning). -
-i
: enable testing (inference). -
-noBoost
: disable Boosting (i.e., learns a single relational regression tree). -
-train <Training directory>
: Path to the training directory in predicate logic format. -
-test <Testing directory>
: Path to the testing directory in predicate logic format format. -
-model <Model directory>
: Path to the directory with the stored models [or where they will be stored].Default location: "Training directory"/models
-
-target <target predicates>
: Comma separated list of predicates to be learned/inferred. -
-trees <Number of trees>
: Number of Boosting trees.Default: 20. Ignored if
-noBoost
is set. -
-step <Step Length>
: Default step length for functional gradient.Default: 1.
-
-modelSuffix <suffix>
: All the trees/models are saved with this suffix appended to the file names. -
-aucJarPath <path to auc.jar>
: If this is not set, AUC values are not computed. -
-testNegPosRatio <Negative/Positive ratio>
: Ratio of negatives to positive for testing.Default: 2. Set to -1 to disable sampling.
Try to follow along with what each of these are doing:
From the Getting Started tutorial:
-
java -jar BoostSRL.jar -l -combine -train train/ -target father -trees 10
-
java -jar BoostSRL.jar -i -model train/models -test test/ -target father -trees 10
From the Boston Housing Dataset (notice the different classpath):
java -cp BoostSRL.jar edu.wisc.cs.will.Boosting.Regression.RunBoostedRegressionTrees -reg -l -train train/ -target medv -trees 20
From the CiteSeer Dataset:
java -jar BoostSRL.jar -l -train train/ -target infield_fauthor,infield_ftitle,infield_fvenue -trees 5
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