In this study, a new Stacked Generalization technique called Fuzzy Stacked Generalization (FSG) is proposed to minimize the difference between N -sample and large-sample classification error of the Nearest Neighbor classifier. The proposed FSG employs a new hierarchical distance learning strategy to minimize the error difference. For this purpose, we first construct an ensemble of base-layer fu...

© 2011 Jang-Hee Yoo and Mark S. Nixon 259 We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: i) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion paramete...

An important but very expensive primitive operation of high-dimensional databases is the KNearest Neighbor (KNN) similarity join. The operation combines each point of one dataset with its KNNs in the other dataset and it provides more meaningful query results than the range similarity join. Such an operation is useful for data mining and similarity search. In this paper, we propose a novel KNN-...

In some regression problems, it may be more reasonable to predict intervals rather than precise values. We are interested in finding intervals which simultaneously for all input instances x ∈ X contain a β proportion of the response values. We name this problem simultaneous interval regression. This is similar to simultaneous tolerance intervals for regression with a high confidence level γ ≈ 1...

Automatic text classification based on vector space model (VSM), artificial neural networks (ANN), Knearest neighbor (KNN), N aives Bayes (NB) and support vector machine (SVM) have been applied on English language documents, and gained popularity among text mining and information retrieval (IR) researchers. This paper proposes the application of ANN for the classification of Tamil language docu...

Introduction: COVID-19 is an acute respiratory illness that directly affects the lungs It much needed to predict possibility of occurrence based on their characteristics Objective: This paper studies different machine learning classification algorithms recovered and deceased cases Methods: The k-fold cross-validation resampling technique used validate prediction model Aim scores each algorithm ...

One of the task of the LAPAN is making obsevation and forecasting of solar storms disturbance. This disturbances can affect the earth's electromagnetic field that disrupt the electronic and navigational equipment on earth. It would be dangerous to human life if not properly anticipated. LAPAN wanted a computer application that can automatically classify the type of solar storms, which became pa...

Although many more complex learning algorithms exist, knearest neighbor (k-NN) is still one of the most successful classifiers in real-world applications. One of the ways of scaling up the k-nearest neighbors classifier to deal with huge datasets is instance selection. Due to the constantly growing amount of data in almost any pattern recognition task, we need more efficient instance selection ...

In a multi script environment, a collection of documents printed in different scripts is in practice. For automatic processing of such documents through Optical Character Recognition, it is necessary to identify the script type of the document. In this paper, a novel texture-based approach is presented to identify the script type of the documents printed in three prioritized scripts Kannada, Hi...

We survey permutation-based methods for approximate knearest neighbor search. In these methods, every data point is represented by a ranked list of pivots sorted by the distance to this point. Such ranked lists are called permutations. The underpinning assumption is that, for both metric and non-metric spaces, the distance between permutations is a good proxy for the distance between original p...