nearest-neighbor classifier
A computer aided detection framework for mammographic images using fisher linear discriminant and nearest neighbor classifier
... A number of researchers have investigated principal component analysis (PCA), Fisher linear discriminant (FLD), and nearest neighbor classifier (KNN) algorithms. For instance, in [6], Hough ...
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FINkNN : A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples
... This work introduces FINkNN, a k-nearest-neighbor classifier operating over the metric lattice of conventional interval-supported convex fuzzy sets. We show that for problems involving populations of ...
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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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Pruned fuzzy K nearest neighbor classifier for beat classification
... K-Nearest Neighbor (SKNN) classifier used in our previous work offers many advantages over other classifiers including simplicity and ease of parallel implementation, adaptability and online learning ...
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Gender Recognition from Faces Using Fuzzy Clustering and Nearest Neighbor Classifier
... Gender recognition based on Weber local descriptor (WLD) [9] is also one of the feature extraction technique, calculates the differential excitation and gradient orientation are integrated to form robust texture ...
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Efficient Surf Tracking by Nearest Neighbor Classifier
... Abstract—Visual object tracking is a fundamental problem in many real applications, like video security surveillance, human computer interaction (HCI), video communication and compression, augmented reality, traffic ...
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Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier
... In numerous (if not all) practical applications, computing the cross-validation (CV) estimator (Stone, 1974, 1982) has been among the most popular strategies to evaluate the performance of the kNN classifier ...
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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 ...each classifier uses a different distance function and potentially ...
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Evaluating the Performance of Dual Weighted K Nearest Neighbor Classifier
... The value of „k' parameter is then decided manually and the weighted Euclidean distances are sorted in ascending order. To reduce the dependency of KNN on „k' parameters instances are assigned weights. This will reduce ...
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LZW Compressed Text Classification using Nearest Neighbor Classifier
... We have proposed a novel method to classify text documents. The proposed method uses LZW compression scheme. Using string matching and nearest neighbor method we have proposed text classification technique. ...
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Feature selection using intensified tabu search for supervised classification
... problems. Nearest Neighbor classifier was used previously as objective ...based classifier; we will explore Naive Bayes Classifier compared with sequential feature selection ...
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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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Normal/Abnormal Gait Analysis based on the Statistical Registration and Modeling of the Frontal View Gait Data
... K-nearest- neighbor classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects ...
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Comparison of Nearest Neighbor (ibk), Regression by Discretization and Isotonic Regression Classification Algorithms for Precipitation Classes Prediction
... of classifier for use in prediction is a ...best classifier comparisons can be made on various aspects of the ...of nearest neighbor (ibk), regression by discretization and isotonic regression ...
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Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform
... Objectives. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. Material and methods. The design phase of the classification model comprises the following stages: ...
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Detection & Classification of Brain Tumour
... ABSTRACT: The use of digital images has become a subject of widespread interest in different areas such as medical technological application and many others. There are lots of examples where image processing helps to ...
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Breast Cancer Computer-aided Diagnosis System from Digital Mammograms
... (K-Nearest Neighbor) classifier, “SVM (Support Vector Machine) classifier, LDA (Linear Discriminant) classifier, QDA (Quadtradic Discriminant Analysis) classifier, NB (Naïve ...
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Crab Gender Classification Using Image Processing, Fuzzy Logic And K Nearest Neighbor (KNN) Classifier
... Abstract: The study aims to determine the gender of a crab with the use of image processing, fuzzy logic, and k-nearest neighbor classifier. The determination of crab gender is usually determined by ...
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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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Efficient Prediction and Classification of Epileptic Seizures Using EEG Data Based on Univariate Linear Features
... Nearest neighbor classifier [14] is a classifier which computes distance of test features from training class features and on the basis of shortest distance it assigns label of that class to ...
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