The distance function effect on k-nearest neighbor classification for medical datasets
نویسندگان
چکیده
منابع مشابه
The distance function effect on k-nearest neighbor classification for medical datasets
INTRODUCTION K-nearest neighbor (k-NN) classification is conventional non-parametric classifier, which has been used as the baseline classifier in many pattern classification problems. It is based on measuring the distances between the test data and each of the training data to decide the final classification output. CASE DESCRIPTION Since the Euclidean distance function is the most widely us...
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Classification of spatial data streams is crucial, since the training dataset changes often. Building a new classifier each time can be very costly with most techniques. In this situation, k-nearest neighbor (KNN) classification is a very good choice, since no residual classifier needs to be built ahead of time. KNN is extremely simple to implement and lends itself to a wide variety of variatio...
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ژورنال
عنوان ژورنال: SpringerPlus
سال: 2016
ISSN: 2193-1801
DOI: 10.1186/s40064-016-2941-7