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weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance))

weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance))

Visibility: public Uploaded 16-08-2018 by Jason Weka_3.4.3 0 runs
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D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).default: ["false"]
AThe nearest neighbour search algorithm to use (default: weka.core.neighboursearch.LinearNNSearch).default: ["weka.core.neighboursearch.LinearNNSearch"]
EMinimise mean squared error rather than mean absolute error when using -X option with numeric prediction.default: ["false"]
FWeight neighbours by 1 - their distance (use when k > 1)default: ["false"]
IWeight neighbours by the inverse of their distance (use when k > 1)default: ["false"]
KNumber of nearest neighbours (k) used in classification. (Default = 1)default: ["1"]
WMaximum number of training instances maintained. Training instances are dropped FIFO. (Default = no window)default: ["0"]
XSelect the number of nearest neighbours between 1 and the k value specified using hold-one-out evaluation on the training data (use when k > 1)default: ["false"]
batch-sizeThe desired batch size for batch prediction (default 100).default: []
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"]

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