New_AdaptiveRandomForest #243
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…orest with an extra option to turn off resampling function. The original is designed to deal with imbalanced datasets.
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Hi Ethan, Cheers, |
| "Defines how m, defined by mFeaturesPerTreeSize, is interpreted. M represents the total number of features.", | ||
| new String[]{"Specified m (integer value)", "sqrt(M)+1", "M-(sqrt(M)+1)", | ||
| "Percentage (M * (m / 100))"}, | ||
| new String[]{"SpecifiedM", "SqrtM1", "MSqrtM1", "Percentage"}, 1); |
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The default value should be 3 in this option
| "Percentage (M * (m / 100))"}, | ||
| new String[]{"SpecifiedM", "SqrtM1", "MSqrtM1", "Percentage"}, 3); | ||
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| "The number of trees.", 10, 1, Integer.MAX_VALUE); |
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The default option should be 100 for the number of trees
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| @Override | ||
| public String getPurposeString() { | ||
| return "Adaptive Random Forest algorithm for evolving data streams from Gomes et al."; | ||
| return "Adaptive Random Forest with Resampling --- beta version"; |
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Please revert the purpose string, there is not need to change it
| public IntOption mFeaturesPerTreeSizeOption = new IntOption("mFeaturesPerTreeSize", 'm', | ||
| "Number of features allowed considered for each split. Negative values corresponds to M - m", 60, Integer.MIN_VALUE, Integer.MAX_VALUE); |
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similar to the other comments, leave these default values as they are
| "The lambda parameter for bagging.", 6.0, 1.0, Float.MAX_VALUE); | ||
| "The lambda parameter for bagging.", 6.0, 1.0, Float.MAX_VALUE); | ||
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| public MultiChoiceOption streamBalanceOption = new MultiChoiceOption("streamBalanceOption", 'r', "The option of stream balance", new String[]{"Imbalance", "Balance"}, |
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This should be the only option added / changed for this PR
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The name would be better if it were classBalancingOption. The options that are displayed on the GUI should be None (No balance) and Balanced and not Imbalance and Balance
| private void init(int indexOriginal, ARFHoeffdingTree instantiatedClassifier, BasicClassificationPerformanceEvaluator evaluatorInstantiated, | ||
| long instancesSeen, boolean useBkgLearner, boolean useDriftDetector, ClassOption driftOption, ClassOption warningOption, boolean isBackgroundLearner) { | ||
| //Option stream/dataset balance or not. Resampling for imbalance, No resampling for balance dataset | ||
| public MultiChoiceOption resampling = streamBalanceOption; |
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Why not use the Option directly? It is not clear why the attribute resampling is needed
I see now why you did it. However, perhaps use a boolean attribute in ARFBaseLearner instead of a MultiChoiceOption. Also, instead of calling it resampling, what about calling balancing, which can be on (true) or off (false).
| this.executor = Executors.newFixedThreadPool(numberOfJobs); | ||
| } | ||
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| @Override | ||
| public void trainOnInstanceImpl(Instance instance) { | ||
| ++this.instancesSeen; | ||
| if(this.ensemble == null) |
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avoid changes to the format of the code, such as adding spaces or extra lines
| this.classifier.resetLearning(); | ||
| this.createdOn = instancesSeen; | ||
| this.driftDetectionMethod = ((ChangeDetector) getPreparedClassOption(this.driftOption)).copy(); | ||
| } | ||
| this.evaluator.reset(); | ||
| } | ||
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| private void populateCounterArray(Instance instnc) { |
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You can call it instance instead of instnc :)
…on as a FlagOption. Modified some default option values.
Comparing with the original AdaptiveRandomForest, New_AdaptiveRandomForest with an extra option to turn off resampling function. The original is designed to deal with imbalanced datasets.