Update DACC and HAT
Merge branch 'master' of https://github.com/abifet/moa
Update DACC
Update change detectors
Add ReplacingMissingValuesFilter
Add ReplacingMissingValuesFilter
Update AMRules from abifet code
Use ClassOption for AMRulesRegressor split criterion
VarianceReduction is now the default split criterion
Debug output updated
Commented some System.out.println lines.
Added Aljaž FIMTDD implementation.
Perceptron fixed
RandomAMRules first commit
Random generator bug fixed.
RandomAMRules, AMRulesRegressor, TargetMean functions, Perceptron
learner now can use instance weights
RandomAMRules can vote using  overal error estimation of the base
learner or weighted sum of the error estimation of the rules
Fixed numAnomaliesDEtected count bug
Fixed RandomAMRules average statistics (model measurements)
Perceptron weight set to 0 if correspondent attributes is not numerical
Added ExpNeg Voting function
RandomRules now has an IntOption to specify a random seed
Isolate AMRules split criteria