Thanks for the answer, I downloaded Prequential AUC, but MoaAuc run and I have an error message and opens the panel of moa, the same as I had. What am i wrong? The error displayed is: Problem with options to 'EvaluatePrequentialRegression'.
Valid options for EvaluatePrequentialRegression:
-l learner (default: trees.FIMTDD)
Classifier to train.
-s stream (default: generators.RandomTreeGenerator)
Stream to learn from.
-e evaluator (default: WindowRegressionPerformanceEvaluator)
Classification performance evaluation method.
-i instanceLimit (default: 100000000)
Maximum number of instances to test/train on (-1 = no limit).
-t timeLimit (default: -1)
Maximum number of seconds to test/train for (-1 = no limit).
-f sampleFrequency (default: 100000)
How many instances between samples of the learning performance.
-q memCheckFrequency (default: 100000)
How many instances between memory bound checks.
-d dumpFile
File to append intermediate csv results to.
-o outputPredictionFile
File to append output predictions to.
-w width (default: 1000)
Size of Window
-a alpha (default: 0.01)
Fading factor or exponential smoothing factor
-O taskResultFile
File to save the final result of the task to.
*** STACK TRACE ***
java.lang.Exception: Problem with options to 'EvaluatePrequentialRegression'.
Valid options for EvaluatePrequentialRegression:
-l learner (default: trees.FIMTDD)
Classifier to train.
-s stream (default: generators.RandomTreeGenerator)
Stream to learn from.
-e evaluator (default: WindowRegressionPerformanceEvaluator)
Classification performance evaluation method.
-i instanceLimit (default: 100000000)
Maximum number of instances to test/train on (-1 = no limit).
-t timeLimit (default: -1)
Maximum number of seconds to test/train for (-1 = no limit).
-f sampleFrequency (default: 100000)
How many instances between samples of the learning performance.
-q memCheckFrequency (default: 100000)
How many instances between memory bound checks.
-d dumpFile
File to append intermediate csv results to.
-o outputPredictionFile
File to append output predictions to.
-w width (default: 1000)
Size of Window
-a alpha (default: 0.01)
Fading factor or exponential smoothing factor
-O taskResultFile
File to save the final result of the task to.
at moa.options.ClassOption.cliStringToObject(ClassOption.java:156)
at moa.gui.RegressionTaskManagerPanel.setTaskString(RegressionTaskManagerPanel.java:380)
at moa.gui.RegressionTaskManagerPanel.<init>(RegressionTaskManagerPanel.java:223)
at moa.gui.RegressionTabPanel.<init>(RegressionTabPanel.java:40)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(Unknown Source)
at java.lang.reflect.Constructor.newInstance(Unknown Source)
at java.lang.Class.newInstance(Unknown Source)
at moa.gui.GUI.initGUI(GUI.java:64)
at moa.gui.GUI.<init>(GUI.java:46)
at moa.gui.GUI$1.run(GUI.java:97)
at java.awt.event.InvocationEvent.dispatch(Unknown Source)
at java.awt.EventQueue.dispatchEventImpl(Unknown Source)
at java.awt.EventQueue.access$500(Unknown Source)
at java.awt.EventQueue$3.run(Unknown Source)
at java.awt.EventQueue$3.run(Unknown Source)
at java.security.AccessController.doPrivileged(Native Method)
at java.security.ProtectionDomain$1.doIntersectionPrivilege(Unknown Source)
at java.awt.EventQueue.dispatchEvent(Unknown Source)
at java.awt.EventDispatchThread.pumpOneEventForFilters(Unknown Source)
at java.awt.EventDispatchThread.pumpEventsForFilter(Unknown Source)
at java.awt.EventDispatchThread.pumpEventsForHierarchy(Unknown Source)
at java.awt.EventDispatchThread.pumpEvents(Unknown Source)
at java.awt.EventDispatchThread.pumpEvents(Unknown Source)
at java.awt.EventDispatchThread.run(Unknown Source)
Caused by: java.lang.IllegalArgumentException: Problems with option: learner
at moa.options.ClassOption.setValueViaCLIString(ClassOption.java:69)
at moa.options.Options.setViaCLIString(Options.java:145)
at moa.options.ClassOption.cliStringToObject(ClassOption.java:154)
... 25 more
Caused by: java.lang.Exception: Problem with options to 'trees.FIMTDD'.
Valid options for trees.FIMTDD:
-a PageHinckleyAlpha (default: 0.005)
The alpha value to use in the Page Hinckley change detection tests.
-h PageHinckleyThreshold (default: 50)
The threshold value to be used in the Page Hinckley change detection tests.
-f AlternateTreeFadingFactor (default: 0.995)
The fading factor to use when deciding if an alternate tree should replace an original.
-y AlternateTreeTMin (default: 150)
The Tmin value to use when deciding if an alternate tree should replace an original.
-u AlternateTreeTime (default: 1500)
The 'time' (in terms of number of instances) value to use when deciding if an alternate tree should be discarded.
-w learningRatio (default: 0.01)
Learning ratio to use for training the Perceptrons in the leaves.
-j learningRatio_Decay_or_Const
learning Ratio Decay or const parameter.
-m maxByteSize (default: 33554432)
Maximum memory consumed by the tree.
-n numericEstimator (default: FIMTDDNumericAttributeClassObserver)
Numeric estimator to use.
-d nominalEstimator (default: NominalAttributeClassObserver)
Nominal estimator to use.
-e memoryEstimatePeriod (default: 1000000)
How many instances between memory consumption checks.
-g gracePeriod (default: 200)
The number of instances a leaf should observe between split attempts.
-s splitCriterion (default: SDRSplitCriterion)
Split criterion to use.
-c splitConfidence (default: 1.0E-7)
The allowable error in split decision, values closer to 0 will take longer to decide.
-t tieThreshold (default: 0.05)
Threshold below which a split will be forced to break ties.
-b binarySplits
Only allow binary splits.
-z stopMemManagement
Stop growing as soon as memory limit is hit.
-r removePoorAtts
Disable poor attributes.
-p noPrePrune
Disable pre-pruning.
-l leafprediction (default: NBAdaptive)
Leaf prediction to use.
-q nbThreshold (default: 0)
The number of instances a leaf should observe before permitting Naive Bayes.
at moa.options.ClassOption.cliStringToObject(ClassOption.java:156)
at moa.options.ClassOption.setValueViaCLIString(ClassOption.java:67)
... 27 more
Caused by: java.lang.IllegalArgumentException: Problems with option: splitCriterion
at moa.options.ClassOption.setValueViaCLIString(ClassOption.java:69)
at moa.options.Options.setViaCLIString(Options.java:145)
at moa.options.ClassOption.cliStringToObject(ClassOption.java:154)
... 28 more
Caused by: java.lang.Exception: Class named 'VarianceReductionSplitCriterion' is not an instance of moa.classifiers.core.splitcriteria.SDRSplitCriterion.
at moa.options.ClassOption.cliStringToObject(ClassOption.java:167)
at moa.options.ClassOption.setValueViaCLIString(ClassOption.java:67)
... 30 more