Flow
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))

weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)))

Visibility: public Uploaded 07-03-2019 by Jan van Rijn Weka_3.9.3 6 runs
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Weka implementation.

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).default: ["false"]
EDetermines the parameter used for evaluation: CC = Correlation coefficient MCC = Matthews correlation coefficient RMSE = Root mean squared error RRSE = Root relative squared error MAE = Mean absolute error RAE = Root absolute error COMB = Combined = (1-abs(CC)) + RRSE + RAE ACC = Accuracy KAP = Kappa PREC = Precision (per class) WPREC = Weighted precision REC = Recall (per class) WREC = Weighted recall AUC = Area under ROC (per class) WAUC = Weighted area under ROC PRC = Area under PRC (per class) WPRC = Weighted area under PRC FM = F-Measure (per class) WFM = Weighted F-Measure TPR = True positive rate (per class) TNR = True negative rate (per class) FPR = False positive rate (per class) FNR = False negative rate (per class) (default: CC)default: ["CC"]
SRandom number seed. (default 1)default: ["1"]
WFull name of base classifier. (default: weka.classifiers.functions.LinearRegression)default: ["weka.classifiers.meta.FilteredClassifier"]
algorithmA search algorithm.default: ["weka.classifiers.meta.multisearch.RandomSearch"]
batch-sizeThe desired batch size for batch prediction (default 100).default: []
class-labelThe class label index to retrieve the metric for (if applicable).default: ["1"]
log-fileThe log file to log the messages to. (default: none)default: ["/home/fr/fr_fr/fr_jv1031"]
num-decimal-placesThe number of decimal places for the output of numbers in the model (default 2).default: []
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the consoledefault: ["false"]
searchA property search setup.default: []

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