• Corpus ID: 14017310

An improved multi-label classification method based on svm with delicate decision boundary

@article{Chen2010AnIM,
  title={An improved multi-label classification method based on svm with delicate decision boundary},
  author={Benhui Chen and Liangpeng Ma and Takayuki Furuzuki},
  journal={International Journal of Innovative Computing Information and Control},
  year={2010},
  volume={6},
  pages={1605-1614}
}
Multi-label classification problem is an extension of traditional multi-class classification problem in which the classes are not mutually exclusive and each sample may belong to several classes simultaneously. Such problems occur in many important applications. Some researches indicate that the performance of classifier can be improved by introducing the information of multi-label training samples into learning procedure effectively. In this paper, we propose a novel method based on SVM with… 
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17 Citations
Background Citations
5
Methods Citations
5

17 Citations

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An improved probabilistic SVM with delicate decision boundary is used as scoring approach to obtain a proper label rank and an instance-dependent thresholding strategy is proposed to decide classification results.
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Malignancy and Abnormality Detection of Mammograms using Classifier Ensembling
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A novel architecture is developed to enhance the classification of malignant and benign mammograms using multi-classification ofmalignant mammograms into six abnormality classes using DWT (Discrete Wavelet Transformation) features.
DCT FEATURES BASED MALIGNANCY AND ABNORMALITY TYPE DETECTION METHOD FOR MAMMOGRAMS
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A novel method which can classify cancerous mammogram into six classes using binary classier (SVM) and using one against all technique for classication is proposed.
A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification
TLDR
This algorithm, called G3P-ML, is evaluated and compared to other multi-label classification techniques in different application domains and shows that it often obtains better results than other algorithms while achieving a lower number of rules than the other methods.
Study on the Predictions of Gene Function and Protein Structure Using Multi-SVM and Hybrid EDA
TLDR
Improved methods based on multi-SVM and hybrid EDA are developed for solving complicated tasks in the predictions of gene function and protein HP model.
SIMILARITY-DISSIMILARITY PLOT FOR HIGH DIMENSIONAL DATA OF DIFFERENT ATTRIBUTE TYPES IN BIOMEDICAL DATASETS
TLDR
The concept of similarity-dissimilarity is extended to various types of attributes and an index called percentage of data points above the similarity-DISSimilarity line (PAS) is proposed which is the fraction of data Points found near to its own class as compared to other classes.
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