Nearest Neighbor (NN) Classifier
Improving nearest neighbor classifier using tabu search and ensemble distance metrics
... The nearest-neighbor (NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining ...of NN classifier. The proposed approach combines ...
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PERBANDINGAN NAIVE BAYES CLASSIFIER DENGAN NEAREST NEIGHBOR UNTUK IDENTIFIKASI PENYAKIT MATA
... AbstrakNaive Bayes Classifier dan Nearest Neighbor merupakan algoritma klasifikasi. Kedua algoritma tersebut dapat dikombinasikan dan dibandingkan untuk mendapatkan akurasi dan kecepatan dalam ...
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Evaluating the Performance of Dual Weighted K Nearest Neighbor Classifier
... One another approach is based on instance weighting technique where the instances get more weight on the basis of their closeness to the new instance than such neighbors that are far away from the new instance had been ...
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Pruned fuzzy K nearest neighbor classifier for beat classification
... K-nearest neighbor (PFKNN) classifier is proposed for beat classifica- ...this classifier is weighted with respect to a priori probabilities of different classes to handle the class imbalance ...
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Heart Disease Classification using Nearest Neighbor Classifier with Feature Subset Selection
... In this section we propose a method for heart disease classification using K-nearest neighbor classifier with optimal feature selection. We used symmetrical uncertainty as a goodness measure to rank ...
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LZW Compressed Text Classification using Nearest Neighbor Classifier
... After giving an effective representation for a document, the task of text classification is to classify the documents to the predefined categories. In order to do so, many statistical and computational models have been ...
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Gender Recognition from Faces Using Fuzzy Clustering and Nearest Neighbor Classifier
... and nearest neighbor, respectively, for feature extraction and classification ...steps. NN also applied to extract the most suitable features from images as well as reducing the dimensionality of ...
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Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier
... kNN classifier can be very different from p = ...kNN classifier, but extends to various estimation/prediction problems (Breiman and Spector, 1992; Arlot and Lerasle, 2012; Celisse, ...
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A Semantic Distance Based Nearest Neighbor Method for Image Annotation
... an NN-based classifier delivering better performance than traditional learning-based ...for NN-based classifier without any information ...
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Efficient Surf Tracking by Nearest Neighbor Classifier
... In this paper we propose using the SURF feature for visual tracking under a tracking-by-detection framework. Compared with [22], we leverage the efficient nearest neighboring criteria [18] and efficient subwindow ...
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Real time Processor for the Authentication of Affected Herbal Medicinal Leaves Using Image Processing Techniques- Review
... the classifier that used Probabilistic Neural Network ...hybrid(composite) classifier by combining two classifiers in common use— classification trees and k- nearest-neighbor ...SVM ...
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Combined Transform domain Based Characterization of Breast Tissues using Nearest Neighbor Classification Techniques
... An evaluation on the performance of CAD systems is done by Sheila Timp et al. 3] with double reading on radiologist‟s diagnostics in classifying benign and malign masses. They conclude that CAD systems with temporal ...
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Comparative Analysis of Eigen face and Sparsity Based Face Recognition Schemes Dr. Renuka Devi S.M, II E. Bhargavi Dept. of Electronics and Communication Engineering, GNITS, Telangana, India.
... between Nearest Neighbor Classifier method using Eigen faces and Sparse Classifier method is considered using a well-known face database which provides better Recognition rates even in various ...
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Evaluating Performance Measures Using Hybrid Models With Fuzzy Finite State Machine For Human Activity Recognition
... k-nearest neighbor classifier is then used as the fitness function in the particle swarm optimization to evaluate the performance of the feature subset, that is, feature combination with the highest ...
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Automatic Detection of Whitefly Pest using Statistical Feature Extraction and Image Classification Methods
... Bayesian classifier, Binary decision tree classifier and k-Nearest neighbor classifier are used to distinguish between healthy leaf images from white fly pest infected leaf ...
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Efficient Prediction and Classification of Epileptic Seizures Using EEG Data Based on Univariate Linear Features
... k-nearest neighbor classifier with different values of k from 1 to ...K-nearest neighbor classifier gives maximum accuracy and true positive rate at ...Bayes classifier ...
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User Navigation Pattern Prediction using Statistical Classifier and Modern Techniques Yogesh Rajaram Bhalerao 1, Prof. P. P. Rokade2
... pairwise nearest neighbor algorithm is used to group the potential clusters and the maximum likelihood classification algorithm with decision tree is to predict users future ...
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Generalized Mean Distance-based k Nearest Centroid Neighbor Classifier
... k nearest neighbor (kNN) is a well-known non-parametric classif8er used in the pattern recognition ...kNN classifier. The selection of nearest neighbor in the kNN is based on the ...
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Hubless Nearest Neighbor Search for Bilingual Lexicon Induction
... est neighbor (NN) in the target space given the source ...improve NN. This work pro- poses a new method, Hubless Nearest Neigh- bor (HNN), to mitigate ...from NN by imposing an ...
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An Effective Method for Online Social Voting Using Collaborative Filtering Based Recommendation Systems
... and nearest neighbor (NN) - based recommender systems (RSs) that investigate client social system and gathering connection data for social choice ...in NN-based ...based NN models ...
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