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When a sample belongs to more than one label from a set of available classes, the classification problem (known as multi-label classification) turns to be more complicated. Text data, widely available nowadays in the world wide web, is an obvious instance example of such a task. This paper presents a new method for multi-label text categorization created by(More)
Artery and vein (AV) classification of retinal images is a key to necessary tasks, such as automated measurement of arteriolar-to-venular diameter ratio (AVR). This paper comprehensively reviews the state-of-the art in AV classification methods. To improve on previous methods, a new Local Binary Pattern-based method (LBP) is proposed. Beside its simplicity,(More)
Please cite this article in press as: Hatami, N. doi:10.1016/j.eswa.2011.07.091 Error-correcting output coding (ECOC) is a strategy to create classifier ensembles which reduces a multiclass problem into some binary sub-problems. A key issue in designing any ECOC classifier refers to defining optimal codematrix having maximum discrimination power and minimum(More)
Error correcting output codes, ECOC, is an output representation method capable of discovering some of the errors produced in classification tasks. This paper describes the application of ECOC to the training of feed forward neural networks, FFNN, for improving the overall accuracy of classification systems. Indeed, to improve the generalization of FFNN(More)
Early classification of time-series data in a dynamic environment is a challenging problem of great importance in signal processing. This paper proposes a classifier architecture with a reject option capable of online decision making without the need to wait for the entire time series signal to be present. The main idea is to classify an odor/gas signal(More)
  • Nima Hatami
  • 2008 Eighth International Conference on…
  • 2008
Cancer classification using gene expression data has the great importance in bioinformatics and is known to contain the keys for addressing the fundamental problems relating to cancer diagnosis and drug discovery. Error correcting output coding (ECOC) is a method to design multiple classifier systems (MCS), which reduces a multi-class problem into some(More)
Hierarchical Text Categorization (HTC) is becoming increasingly important with the rapidly growing amount of text data available in the World Wide Web. Among the different strategies proposed to cope with HTC, the Local Classifier per Node (LCN) approach attains good performance by mirroring the underlying class hierarchy while enforcing a top-down strategy(More)
Acknowledgements It is a great pleasure to thank those people whose company I enjoyed in my lovely PhD journey. It is difficult to overstate my gratitude to my friend and Ph.D. supervisor, Prof. Giuliano Armano. During these three years, he gave me an opportunity to learn not only how to be a thinker but most importantly be a life lover. Working with him(More)