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A Simple and Fast Multi-instance Classification via Support Vector ...
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Abstract: In this paper, we proposed a Simple and Fast Multi-Instance Classification Via Support Vector Machine (called Fast MI-SVM).
Abstract—In this paper, we proposed a Simple and. Fast Multi-Instance Classification Via Support Vector Ma- chine(called FastMI-SVM).
Compared with the other conventional Multi-Instance learning method, this method is able to deal with multi-instance learning problem by only solving a ...
In this paper, we proposed a Simple and Fast Multi-Instance Classification Via Support Vector Machine(called Fast MI-SVM).
This paper presents a new formulation of multi-instance learning as maximum margin problem, which is an extension of the standard C-support vector ...
MISVM contains a Python implementation of numerous support vector machine (SVM) algorithms for the multiple-instance (MI) learning framework.
Missing: Simple Fast
We present a newly developed IS method called Valid Border Recognition (VBR). VBR selects the closest heterogeneous neighbors as valid border instances.
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This paper presents two new formulations of multiple-instance learning as a maximum margin problem. The proposed extensions of the Support Vector Machine ...
Missing: Fast | Show results with:Fast
The mildsvm package provides an easy way to learn from this data by training Support Vector Machine (SVM)-based classifiers.
This paper presents an instance selection method especially for multi-class problems. With cluster centers of positive class as reference points instances are ...