<NME> exp211.properties
<BEF> ADDFILE
<MSG> Exp211 supports hybrid mixture model

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+input.trainData=/scratch/wang.bin/trec.data/tmc2007-500/data_sets/train
+input.testData=/scratch/wang.bin/trec.data/tmc2007-500/data_sets/test
+# sparse_random or sparse_sequential
+# sparse_sequential should be avoided when boosting is used
+input.matrixType=sparse_random
+
+output=/scratch/wang.bin/pyramid/exp211/tmc2007-500
+saveModel=true
+saveModelForEachIter=true
+modelName=c10.1.1.0.6.model
+
+mixture.numClusters=10
+mixture.multiClassClassifierType=boost
+mixture.binaryClassifierType=lr
+
+
+train.warmStart=false
+train.initialize=true
+
+predict.mode=dynamic
+# if sampling
+predict.sampling.numSamples=100
+# whether allow empty set to be the prediction
+predict.allowEmpty=false
+
+########## EM ###########
+em.inverseTemperature=1.0
+em.numIterations=1000
+
+####### logistic regression #####
+lr.multiClassVariance=1.0
+lr.binaryVariance=1.0
+# always false 
+lr.meanRegularization=false
+lr.meanRegVariance=1.0
+
+############# boosting #########
+# in each M step
+boost.numIterationsBinary=20
+boost.numIterationsMultiClass=20
+boost.numLeavesBinary=2
+boost.numLeavesMultiClass=2
+boost.shrinkageBinary=0.1
+boost.shrinkageMultiClass=0.1
+
+

Exp211 supports hybrid mixture model