nearest neighbor pattern classifier
Sound Recognition of Induction Motor
... In this paper numerical experiments are proposed to investigate differences between the acoustic signals of induction motors. Four conditions of induction motor were considered. Investigations were carried out with ...
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PERBANDINGAN NAIVE BAYES CLASSIFIER DENGAN NEAREST NEIGHBOR UNTUK IDENTIFIKASI PENYAKIT MATA
... Langkah berikutnya adalah menyiapkan pola gejala Penyakit Mata yang baru untuk dibandingkan dengan gejala umum penyakit mata (Pattern Preparing). Gejala Penyakit Mata yang telah diklasifikasi di-insert ke dalam ...
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Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning
... margin nearest neighbor classification (LMNN) is one of the most popular techniques in the metric learning zoo [12, 1, 9], which specifically aims to improve the accuracy of a k-nearest ...
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Heart Disease Classification using Nearest Neighbor Classifier with Feature Subset Selection
... Feature subset selection is a preprocessing commonly used in machine learning, where subset of features available from the data is selected for application of a learning algorithm. The subset contains the least no. of ...
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Gender Recognition from Faces Using Fuzzy Clustering and Nearest Neighbor Classifier
... Face is known as one of the most compelling biometric features used to analyze different people. Identifying familiar faces, derive information such as gender, race and affecting state from a face are some detail of ...
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Efficient Surf Tracking by Nearest Neighbor Classifier
... Local invariant features exhibit competitive performance in computer vision and pattern recognition tasks thanks to their appealing representation characteristics. [7] gives a thorough empirical study on the ...
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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 ...
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Comparative Analysis Of Advanced Classification Techniques For Multilingual Ocr Systems
... k-Nearest Neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Local Binary Pattern ...ANN classifier and in SVM for ...
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A modified k-nearest neighbor classifier to deal with unbalanced classes
... An important aspect of many classification problems is that patterns are often not equally distributed among classes, and the different classes may vary in their degrees of importance. For instance, in medical diagnosis ...
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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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A Novel Approach to Enhance the Performance of Web Log Classification
... used pattern discovery methods is the classification of weblog data ...tree classifier (J48), K nearest neighbor (KNN) and many ...base classifier within a single prediction by training ...
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Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier
... Many researchers have used Freeman chain code for extracting features of characters or numerals due to its simplicity and the capability for small memory requirement. K-Nearest Neighbors (KNN) was also used ...
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A GIS Approach to Evaluation of Accessibility to Private Primary Schools in Ilorin West Local Government Area, Kwara State, Nigeria Oloko-oba O. Mustapha* 1, Haruna L. Rakiat2 , Okeke U. Henry 3, Olowojoba O. Success4 Alwadood J. Ali 5Olaoluwa A. Idayat6
... In most cases, measures of accessibility include both an impedance factor, reflecting the time or cost of reaching a destination, and an attractiveness factor, reflecting the qualities of the potential destinations. ...
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When Is Nearest Neighbor Meaningful?
... well-defined nearest neighbor, the difference in distance between the nearest neighbor and any other point in the data set is very ...a nearest neighbor is impossible with any ...
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Efficient discriminative learning of parametric nearest neighbor classifiers
... the analysis of the Gaussian kernel density estimation, and attempt to learn the prototypes for nearest neighbor search and the classifier parameters jointly and discriminatively. The decision boundary of ...
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A Comparative Study of Simple Online Learning Strategies for Streaming Data
... Although the general behavior of the rest of clas- sifiers is similar to that of the quadratic, it worths pointing out that the error rates of 1-NN, the linear discriminant, the decision tree, and the Na¨ıve Bayes ...
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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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Pattern Recognition Using K-Nearest Neighbors (KNN) Technique
... During early phase of this project, literature research has to be made in order to gather the information about the current classifier system and their weaknesses. Initially, the author will use alphabets as ...
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Detection & Classification of Brain Tumour
... With the growing population, cancer has become a global public health problem. According to the World Cancer Researcher, cancer is the world’s first cause of death. The incidence of brain tumors is rapidly increasing in ...
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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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