Machine Learning ppt

... words correctly classified 4 MACHINE LEARNING Artificial intelligence Learning symbolic representations of concepts. Machine learning as a search problem. Learning as an approach to improving ... arises. 1.1 WELL-POSED LEARNING PROBLEMS Let us begin our study of machine learning by considering a few learning tasks. For the purposes of this book we will define lear...

Ngày tải lên: 29/03/2014, 12:20

... attempt to write a comprehensive catalog covering the entire spectrum of machine learning techniques, but rather to focus on the learning methods that are powerful and effective for modeling multimedia ... algorithm Contents 1 Introduction 1 1.1 Basic Statistical Learning Problems . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Categorizations of Machine Learning Techniques ....

Ngày tải lên: 14/02/2014, 12:20

... to unsupervised learning to overcome the lack of training data. However their model also has the same problem. McDonald (McDonald, 2006) independently proposed a new machine learning approach. ... former problem, we apply a maxi- mum entropy model to Knight and Marcu’s model to introduce machine learning features that are de- fined not only for CFG rules but also for other characteri...

Ngày tải lên: 20/02/2014, 12:20

... select these learning- based coreference systems and acquire the ranking model. 3.1 Selecting Coreference Systems A learning- based coreference system can be defined by four elements: the learning algorithm ... generate good can- didate partitions. Given that machine learning ap- proaches to the problem have been promising, our choices will be guided by previous learning- based corefe...

Ngày tải lên: 20/02/2014, 15:20

... state-of-the-art and poised to build the next generation of machine learning algorithms.” David Blei, Princeton University machine learning Machine Learning A Probabilistic Perspective Kevin P. Murphy Today’s ... practitio- ners of modern machine learning. It covers the basic concepts needed to understand the field as a whole, and the powerful modern methods that build on th...

Ngày tải lên: 06/03/2014, 03:20

... 4). In a Machine Learning context, Perlich et al. (2003) used learning curves for predicting maximum performance bounds of learning algorithms and to compare them. In Gu et al. (2001), the learning curves ... a x −α is a good model of the learning curves. Learning curves are also frequently used for de- termining empirically the number of iterations for an incremental learning...

Ngày tải lên: 07/03/2014, 18:20

... 27–35, Suntec, Singapore, 4 August 2009. c 2009 ACL and AFNLP Paraphrase Recognition Using Machine Learning to Combine Similarity Measures Prodromos Malakasiotis Department of Informatics Athens ... correspond to machine translation evaluation metrics, rather than string similarity measures, unlike our system. We plan to examine further how the features of Finch et al. and other ideas...

Ngày tải lên: 08/03/2014, 01:20

... three generic machine learning algorithms: a memory-based learner (Daelemans and van den Bosch, 2005), a maxi- mum entropy classifier (Berger et al., 1996) and a Support Vector Machine classifier ... the machine- learning- based method avoids some sparse data problems and al- lows for more control over Cast3LB tag assign- ment. We have found that the SVM algorithm out- performs the othe...

Ngày tải lên: 08/03/2014, 02:21

... studies suggest that machine learn- ing can be applied to develop good auto- matic evaluation metrics for machine trans- lated sentences. This paper further ana- lyzes aspects of learning that impact ... criteria. Machine learning af- fords a unified framework to compose these crite- ria into a single metric. In this paper, we have demonstrated the viability of a regression approach...

Ngày tải lên: 08/03/2014, 02:21

... University of Maryland statistical machine trans- lation system for the Fourth Workshop on Machine Trans- lation. In Proceedings of the Fourth Workshop on Statisti- cal Machine Translation, pages 145–149, ... Machine Translation, pages 145–149, Athens, Greece, March. Jason Eisner. 2003. Learning Non-Isomorphic tree mappings for Machine Translation. In Proc. ACL-2003, pages 205– 20...

Ngày tải lên: 17/03/2014, 00:20