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the optimized featuresetto maximize the k - nearest - neighbor classifier performance
a distancemetric learnerdesignedfor -nearest neighbor ( kNN ) classifier
Kalman prediction ... to helpsettingtracking cluster through nearest neighbor criterion
RCreatesan efficient k nearest neighbor estimator for functional data classification
selection of referencesetfor the k - nearest neighbor classifier
pricing in CADCreatea Knn ( K nearest neighbor ) model to predict feature 6 days
the datasetfor enhanced K - nearest neighbor , k - nearest neighbor and Bayesian classification method
The trainingsetfor the K - nearest - neighbor classifier
ExhaustiveSearcher(X,'Distance','chebychevcreatesan exhaustive nearest neighbor searcher object that uses the Chebychev distance
in 100 % sensitivity and a specificity of 83 % ( accuracy 91 %resultedin 100 % sensitivity and a specificity of 83 % ( accuracy 91 %
to solve traditional ML problem with 2 KB sized modelsis designedto solve traditional ML problem with 2 KB sized models
A simplified version of the approach proposed in this paper participated in PAN at CLEF 2014 Authorship Identification competitionsetA simplified version of the approach proposed in this paper participated in PAN at CLEF 2014 Authorship Identification competition
Much effort(passive) had been contributedMuch effort
to answer the questiondesignedto answer the question
the accuracy of the systeminfluencesthe accuracy of the system
This curve(passive) is createdThis curve
a classification model that performs k - nearest neighbor classificationcreatesa classification model that performs k - nearest neighbor classification
a graph based on the distance between all pairs of points in the data set andcreatea graph based on the distance between all pairs of points in the data set and