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ON THE ARCHITECTURE OF A BIG DATA CLASSIFICATION TOOL BASED ON A MAP REDUCE APPROACH FOR HYPERSPECTRAL IMAGE ANALYSIS

ON THE ARCHITECTURE OF A BIG DATA CLASSIFICATION TOOL BASED ...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： V. A. Ayma R. S. Ferreira P. N. Happ D. A. B. Oliveira G. A. O. P. Costa R. Q. Feitosa A. Plaza P. Gamba Dept. of Electrical Engineering Pontifical Catholic University of Rio de Janeiro Dept. of Technology of Computers and Communications University of Extremadura Dept. of Electronics University of Pavia

ISBN: (纸本)9781479979301

Advances in remote sensors are providing exceptional quantities of large-scale data with increasing spatial, spectral and temporal resolutions, raising new challenges in its analysis, e.g. those presents in classification processes. This work presents the architecture of the InterIMAGE Cloud Platform (ICP): Data Mining Package;a tool able to perform supervised classification procedures on huge amounts of data, on a distributed infrastructure. The architecture is implemented on top of the MapReduce framework. The tool has four classification algorithms implemented taken from WEKA's machine learning library, namely: Decision Trees, Naive Bayes, Random Forest and Support Vector Machines. The SVM classifier was applied on datasets of different sizes (2 GB, 4 GB and 10 GB) for different cluster configurations (5, 10, 20, 50 nodes). The results show the tool as a potential approach to parallelize classification processes on big data.

关键词： MapReduce Big Data Classification algorithms Cloud Computing big data ARCHITECTURE Cloud Computing Building construction sorting algorithm Support Vector Network image analysis Remote sensing equipment temporal resolution Decision Trees

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Semi-Supervised Sleep-Stage Scoring Based on Single Channel EEG

Semi-Supervised Sleep-Stage Scoring Based on Single Channel ...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： A. M. Munk K. V. Olesen S. W. Gangstad L. K. Hansen Technical University of Denmark Department of Applied Mathematics and Computer Science DK-2800 Kongens Lyngby Denmark

ISBN: (纸本)9781538646595

The field of automatic sleep stage classification based on EEG has enjoyed substantial attention during the last decade, which has resulted in several supervised classification algorithms with highly encouraging performance. Such supervised machine learning algorithms require large training sets that have been manually labelled, and are time- and resource-consuming to acquire. Here we present a semi-supervised approach that can learn to distinguish the sleep stages from a one-night data set where only a fraction has been manually labelled. We show that for fractions larger than 50%, our semi-supervised approach performs as good as a similar, fully-supervised model.

关键词： EEG semi-supervised learning sleep stage scoring non-negative matrix factorizaton generalizable Gaussian mixture model Electroencephalography Semi-supervised Learning Scoring Scoring Manual handling Sleep Stages sorting algorithm

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CENTROID-BASED TEXTURE CLASSIFICATION USING THE SIRV REPRESENTATION

CENTROID-BASED TEXTURE CLASSIFICATION USING THE SIRV REPRESE...

引用

IEEE International Conference on Image Processing

作者： Aurélien Schutz Lionel Bombrun Yannick Berthoumieu Université de Bordeaux ENSEIRB-Matmeca Laboratoire IMS Groupe Signal et Image

ISBN: (纸本)9781479923427

This paper introduces a centroid-based (CB) supervised classification algorithm of textured images. In the context of scale/orientation decomposition, we demonstrate the possibility to develop centroid approach based on multivariate stochastic modeling. The main interest of the multivariate modeling comparatively to the univariate case is to consider spatial dependency as additional features for characterizing texture content. The aim of this paper is twofold. Firstly, we introduce the Spherically Invariant Random Vector (SIRV) representation for the modeling of wavelet coefficients. Secondly, from the specific properties of the SIRV process, i.e. the independence between the two sub-processes of the compound model, we derive centroid estimation scheme. Experiments from various conventional texture databases are conducted and demonstrate the interest of the proposed classification algorithm.

关键词： textured images Jeffrey divergence SIRV model centroid supervised classification Centroid sorting algorithm textures additional features specific properties

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Design and Implementation of Targeting Advertising System based on C4.5 algorithm

Design and Implementation of Targeting Advertising System ba...

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International Conference on Computer Science and Network Technology

作者： Xuefei Wang Yan Shi The Open University of Harbin

ISBN: (纸本)9781467381741

With the development of Big data, cloud storage and data mining, targeting advertising technology has aroused wide attention. So many companies have invested in the target mobile advertising market in this area. Targeting advertising can effectively save resources, reduce capital investment. Aiming at this problem, this paper proposed a new method for targeting advertising based on C4.5 algorithm and cloud storage. The mess data about users, such as user information, user browsing behavior and so on, is stored in the cloud. With C4.5 algorithm, we do mess data processing for data classification. Then, with the results of classification, the server-push blocks push targeted advertising for users. This paper introduces the structure of the system and the detailed analysis of the classification algorithm. And the classification results obtained in this paper are compared with those by other algorithms. It is believed that this paper will be helpful in the development of targeting advertising.

关键词： target advertising Big data C4.5 algorithm big data Advertising as Topic targeting sorting algorithm data classification pushing Cloud Computing paper Consumers

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A Reduction from Apprenticeship Learning to Classification 10

A Reduction from Apprenticeship Learning to Classification

引用

Annual Conference on Neural Information Processing Systems

作者： Umar Syed Robert E. Schapire Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104 Department of Computer Science Princeton University Princeton NJ 08540

ISBN: (纸本)9781617823800

We provide new theoretical results for apprenticeship learning, a variant of reinforcement learning in which the true reward function is unknown, and the goal is to perform well relative to an observed expert. We study a common approach to learning from expert demonstrations: using a classification algorithm to learn to imitate the expert's behavior. Although this straightforward learning strategy is widely-used in practice, it has been subject to very little formal analysis. We prove that, if the learned classifier has error rate ∈, the difference between the value of the apprentice's policy and the expert's policy is O(∈~(1/2)). Further, we prove that this difference is only O(∈) when the expert's policy is close to optimal. This latter result has an important practical consequence: Not only does imitating a near-optimal expert result in a better policy, but far fewer demonstrations are required to successfully imitate such an expert. This suggests an opportunity for substantial savings whenever the expert is known to be good, but demonstrations are expensive or difficult to obtain.

关键词： Apprenticeship Learning sorting algorithm formal analysis Policies

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A Pattern Recognition Approach for Enhancing Lifecycle Maintainability of Battery Systems

A Pattern Recognition Approach for Enhancing Lifecycle Maint...

引用

IEEE International Symposium on Systems Engineering (ISSE)

作者： R. Pirani J. Cale Department of Systems Engineering Colorado State University Fort Collins CO USA

This paper introduces an approach for pre-screening manufactured batteries before system deployment, with the goal of reducing higher lifecycle maintenance costs attributed to failure-prone batteries. The method employs a pattern recognition algorithm for classifying parts for acceptance or rejection. The paper describes the classification algorithm and demonstrates its performance on example pre-acceptance test data. Using an example system maintenance concept, the economic and operational impacts of the classification are also demonstrated.

关键词： battery management systems cost reduction failure analysis maintenance engineering pattern classification power engineering computing reliability secondary cells Battery management systems Power engineering computing Secondary batteries Maintenance engineering Batteries Pattern recognition COST REDUCTION FAILURE ANALYSIS sorting algorithm Life cycle pattern recognition method pictorial pattern recognition algorithm

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Abnormal objective recognition in video based on data mining of finance industry

Abnormal objective recognition in video based on data mining...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhi-Wang Jiang Hong-Xia Zhang Financial Intelligence Application Technology R&D- Center of Hebei Province Baoding China

ISBN: (纸本)9781467372220

In order to strengthen the financial industry security, this paper puts forward an intelligent monitoring system which has the function of abnormal automatic moving object recognition based on data mining technology. First of all, this paper elaborates the common classification of data mining methods, through the experiment and comparison, and selects associative classification algorithm for mining algorithm; Secondly, based on support and confidence level optimization, the associative classification algorithm is proposed, and simulation experiment shows that this method is effective to overcome the experience in accordance with the values given threshold caused adverse effect; Finally, the intelligent monitoring system consists of data mining system and the user's system. It is not only to achieve the purpose of the intelligent monitoring, but also to achieve a good human-computer interaction.

关键词： Associative classification Confidence level Data mining Object recognition Support data mining object recognition sorting algorithm Videotapes data mining system simulation test Support Associative

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Segmentation algorithms of Chromosome Images

Segmentation Algorithms of Chromosome Images

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International Conference on Computer Science and Network Technology

作者： Wenzhong Yan Dongming Li Dept. of Comput. North China Inst. of Sci. & Technol. Beijing China

ISBN: (纸本)9781479905607

The chromosome segmentation is the most important step in the automatic chromosome analysis system. In this paper, a few basic chromosome segmentation algorithms are investigated firstly. As a common phenomenon, the partial touching and overlapping chromosomes occur in almost every metaphase images. So, as a difficult yet vital problem, the algorithms for overlapping chromosomes are discussed in detail. The principle and the realization of these algorithms are analyzed. Results of these algorithms are compared and discussed.

关键词： biology computing cellular biophysics image segmentation automatic chromosome analysis system chromosome images chromosome segmentation algorithm metaphase image overlapping chromosomes partial touching chromosomes segmentation algorithms Accuracy algorithm design and analysis Biological cells Classification algorithms Entropy Image segmentation Shape chromosome overlapping segmentation image segmentation algorithm design and analysis Chromosomes biology computing cellular biophysics cytology sorting algorithm segmentation Segmentation entropy

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AN INVESTIGATION ON BACK-END FOR SPEAKER RECOGNITION IN MULTI-SESSION ENROLLMENT

AN INVESTIGATION ON BACK-END FOR SPEAKER RECOGNITION IN MULT...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Gang Liu Taufiq Hasan Hynek Boril John H.L. Hansen Center for Robust Speech Systems (CRSS) Erik Jonsson School of Engineering and Computer Science University of Texas at Dallas Richardson Texas 75083 USA

ISBN: (纸本)9781479903573

This study explores various back-end classifiers for robust speaker recognition in multi-session enrollment, with emphasis on optimal utilization and organization of speaker information present in the development data. Our objective is to construct a highly discriminative back-end framework by fusing several back-ends on an i-vector system framework. It is demonstrated that, by using different information/data configuration and modeling schemes, performance of the fused system can be significantly improved compared to an individual system using a single front-end and back-end. Averaged across both genders, we obtain a relative improvement in EER and minDCF by 56.5% and 49.4%, respectively. Consistent performance gains obtained using the proposed strategy validates its effectiveness. This system is part of the CRSS' NIST SRE 2012 submission system.

关键词： Universal Background Support PLDA speaker recognition GCDS classification algorithms Loudspeakers back-end sorting algorithm speaker recognition individual system front-ends energy efficiency ratio

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Malicious Web Content Detection Using Machine Leaning

Malicious Web Content Detection Using Machine Leaning

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IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology

作者： Anand Desai Janvi Jatakia Rohit Naik Nataasha Raul Sardar Patel Institute of Technology

ISBN: (纸本)9781509037056

Naive users using a browser have no idea about the back-end of the page. The users might be tricked into giving away their credentials or downloading malicious data. Our aim is to create an extension for Chrome which will act as middleware between the users and the malicious websites, and mitigate the risk of users succumbing to such websites. Further, all harmful content cannot be exhaustively collected as even that is bound to continuous development. To counter this we are using machine learning- to train the tool and categorize the new content it sees every time into the particular categories so that corresponding action can be taken.

关键词： Feature extraction Uniform resource locators Classification algorithms algorithm design and analysis Tools Prediction algorithms Uniform Resource Locator algorithm design and analysis Prediction algorithms sorting algorithm Feature extraction Consumers chromium Web page content Credentialing

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