نتایج جستجو برای: neighborhood bayes algorithm
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In recent years during the pandemic Wikipedia created more than 5,200 new pages regarding COVID-19 cases, with an accumulation of 400 million by mid-June 2020. is one most popular websites our time. this case always integrates and fast research. To get opinion from wikipedia text, sentiment analysis needed. The was conducted using a classification containing public issue in Indonesia. method us...
In this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. In this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. To tackle the problem efficiently and effectively, an effici...
A reduce algorithm based on the neighborhood granulation and niche Particle Swarm Optimization (PSO) algorithm is proposed for the reduction of the real decision system with numerical attributes. In this scheme, a rough model is used based on the neighborhood equivalence. The indiscernibility relation is measured by the neighborhood relation, and the universe spaces are approximated by the neig...
Introduction: Diabetes or diabetes mellitus is a metabolic disorder in body when the body does not produce insulin, and produced insulin cannot function normally. The presence of various signs and symptoms of this disease makes it difficult for doctors to diagnose. Data mining allows analysis of patients’ clinical data for medical decision making. The aim of this study was to provide a model fo...
This paper presents an algorithmic framework for feature selection, which selects a subset of features by minimizing the nonparametric Bayes error. A set of existing algorithms as well as new ones can be derived naturally from this framework. For example, we show that the Relief algorithm greedily attempts to minimize the Bayes error estimated by k-Nearest-Neighbor method. This new interpretati...
Data mining applications require learning algorithms to have high predictive accuracy, scale up to large datasets, and produce compre-hensible outcomes. Naive Bayes classiier has received extensive attention due to its eeciency, reasonable predictive accuracy, and simplicity. However , the assumption of attribute dependency given class of Naive Bayes is often violated, producing incorrect proba...
Urban neighborhoods are a unique form of geography in that their boundaries rely on a social definition rather than a well-defined physical or administrative boundary. Currently, geographic gazetteers capture little more than then the centroid of a neighborhood, limiting potential applications of the data. In this paper, we present μ-shapes, an algorithm that employs fuzzy-set theory to model n...
The context tree model has the property that occurrence probability of symbols is determined from a finite past sequence and broader class sources includes i.i.d. or Markov sources. This paper proposes non-stationary source with models change interval to interval. Bayes code for this requires weighting posterior probabilities points, so computational complexity it usually increases exponential ...
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