شماره ركورد كنفرانس :
3297
عنوان مقاله :
Multi-label Classification Systems by the Use of Supervised Clustering
عنوان به زبان ديگر :
Multi-label Classification Systems by the Use of Supervised Clustering
پديدآورندگان :
Rastin Niloofar School of Electrical and Computer Engineering Shiraz University , zolghadri jahromi Mansoor School of Electrical and Computer Engineering Shiraz University , Taheri Mohammad School of Electrical and Computer Engineering Shiraz University
كليدواژه :
supervised clustering , label correlations , Terms— multi-label classification
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
Multi-label classification problem involves finding
a model that maps a set of input features to more than one
output labels. It is well known that, exploiting label correlations
is important for multi-label learning. In this paper, a supervised
clustering-based multi-label classification method is proposed
that uses supervised clustering for considering label correlations.
The proposed approach enhanced the performance of multi-label
classification systems in comparison with the state of the art.
Experimental results on a number of image, music and text
datasets validate the effectiveness of the proposed approach.
