PENGEMBANGAN SISTEM PAKAR DIAGNOSA PENYAKIT SAPI POTONG DENGAN METODE FUZZY K-NEAREST NEIGHBOUR
نویسندگان
چکیده
منابع مشابه
k-Nearest Neighbour Classifiers
Perhaps the most straightforward classifier in the arsenal or machine learning techniques is the Nearest Neighbour Classifier – classification is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance today because issues of poor run-time performance is not such...
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A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar’s fuzzyrough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the exp...
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Random k-nearest-neighbour (RKNN) imputation is an established algorithm for filling in missing values in data sets. Assume that data are missing in a random way, so that missingness is independent of unobserved values (MAR), and assume there is a minimum positive probability of a response vector being complete. Then RKNN, with k equal to the square root of the sample size, asymptotically produ...
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ژورنال
عنوان ژورنال: Journal of Enviromental Engineering and Sustainable Technology
سال: 2015
ISSN: 2356-3117
DOI: 10.21776/ub.jeest.2015.002.01.8