A Joint Spectral Similarity Measure for Graphs Classification
نویسندگان
چکیده
منابع مشابه
Using a similarity measure for credible classification
This paper concerns classification by Boolean functions. We investigate the classification accuracy obtained by standard classification techniques on unseen points (elements of the domain, {0, 1}(n), for some n) that are similar, in particular senses, to the points that have been observed as training observations. Explicitly, we use a new measure of how similar a point x in {0, 1}(n) is to a se...
متن کاملA Similarity Measure for Automatic Audio Classification
This paper presents recent results using statistics generated by a MMl-supervised vector quantizer as a measure of audio similarity. Such a measure has proved successful for talker identification, and the extension from speech to general audio, such as music, is straightforward. A classifier that distinguishes speech from music and non-vocal sounds is presented, as well as experimental results ...
متن کاملA Trainable Similarity Measure for Image Classification
In object recognition problems a two-stage system is usually adopted composed of a fast and simple detector and a more complex classifier. This paper studies a design of the second stage classifier based on the recently proposed trainable similarity measure which is specifically designed for supervised classification of images. Common global measures such as correlation suffer from uninformativ...
متن کاملMap Classification with a Similarity Measure
In many methods of knowledge discovery, data mining and machine learning, similarities between objects are one of the most important factors. In this paper, we require a similarity measure to have (1) clear meaning of the quantity and (2) adaptability to target problems. We propose a similarity measure that yields maximum a posteriori classification. This similarity measure is based on a belief...
متن کاملsimilarity measure for two densities
scott and szewczyk in technometrics, 2001, have introduced a similarity measure for twodensities f1 and f2 , by1, 21 21 1 2 2( , ), ,f fsim f ff f f f< >=< >< >wheref1, f2 f1(x, θ1)f2(x, θ2)dx.+∞−∞< >=∫sim(f1, f2) has some appropriate properties that can be suitable measures for the similarity of f1 and f2 .however, due to some restrictions on the value of parameters and the kind of densities, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Pattern Recognition Letters
سال: 2019
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2018.12.014