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检索条件"主题词=Sorting algorithm"

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SVM is not always confident: Telling whether the output from multiclass SVM is true or false by analysing its confidence values 16

SVM is not always confident: Telling whether the output from...

引用

2014 16th IEEE International Workshop on Multimedia Signal Processing, MMSP 2014

作者： Yamasaki, Toshihiko Maeda, Takaki Aizawa, Kiyoharu Department of Information and Communication Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan

ISBN: (纸本)9781479958962

This paper presents an algorithm to distinguish whether the output label that is yielded from multiclass support vector machine (SVM) is true or false without knowing the answer. Such judgment is done only by the confidence analysis based on the pre-training/testing using the training data. Such true/false judgment is useful for refining the output labels. We experimentally demonstrate that the decision value difference between the top candidate and the second candidate is a good measure. In addition, a proper threshold can be determined by the pre-training/testing using only the training data. Experimental results using three standard image datasets demonstrate that our proposed algorithm can improve Matthews correlation coefficient (MCC) much better than simply thresholding the decision value for the top candidate.

关键词： data analysis support vector machines MCC Matthews correlation coefficient confidence analysis confidence values decision value difference decision value thresholding false judgment image datasets multiclass SVM multiclass support vector machine output label true judgment Accuracy Classification algorithms Machine learning algorithms Support vector machines Testing Training Training data Support Vector Network Training data Machine learning algorithms sorting algorithm MCC Genes False multi-class Functional training

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A Novel pattern recognition model for real-time voice data input 5

A Novel pattern recognition model for real-time voice data i...

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5th International Conference on Confluence 2014 - The Next Generation Information Technology Summit

作者： Sen, Yogesh Kumar Chaurasiya, R.K. Verma, Shrish Dept. of Electronics and Telecommunication National Institute of Technology Raipur India

ISBN: (纸本)9781479942367

The classical front end analysis in speech recognition is a spectral analysis which parameterizes the speech signal into feature vectors. This paper proposes a voice recognition model that is able to automatically classify and recognize a voice signal with background noise. The model uses the concept of spectrogram, pitch period, short time energy, zero crossing rate, mel frequency scale and cepestral coefficient in order to calculate feature vectors. The k-Nearest Neighbor (k-NN) classification is used for classification and recognition of real-time input signal. Analytical hierarchical process is used for deciding the weightage of different features.

关键词： Accuracy Classification algorithms Real-time systems Speech Speech recognition Training AHP k-nearest neighbor pattern classification pitch-period Speech recognition Pattern recognition Voice Signal sorting algorithm real-time systems Analytic hierarchy process Speech Functional training k nearest neighbor audio data Training

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Advanced Pseudo-inverse Linear Discriminants for the Improvement of Classification Accuracies

Advanced Pseudo-inverse Linear Discriminants for the Improve...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jin Zhichao Guo Lili Gao Daqi East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9781509061822

There is very little practicable significance to prove the equivalency between a pseudo-inverse linear discriminant (PILD) with the desired outputs in reverse proportion to the number of within-class samples and a Fisher linear discriminant (FLD) with the totally projected mean thresholds which are disadvantageous to improve the overall classification accuracy. Even if so, several examples have borne out that a PILD is not wholly equivalent to an FLD. Consequently, the most often used total-projected-mean thresholds usually behave poor. Starting from the customarily desired targets {1, -1}, a simple practicable threshold is gotten, which is only related to sample sizes. By substituting the desired targets with the actually algebraic distances of all training samples, a new threshold is obtained. When the desired targets are different from each other, the weight vector and the threshold given by a PILD are not equal to the ones given by an FLD anymore. At the moment, a PILD is wholly different from an FLD.

关键词： Training Classification algorithms Mathematical model Computer science Electronic mail Linear discriminant analysis algorithm design and analysis algorithm design and analysis electronic mail sorting algorithm computer science Linear discriminant analysis Mathematical Model Functional training Gemfibrozil gotten weight vectors Training

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Using Implicit Job Seeker Preferences To Improve Job Recommendation Ranking

Using Implicit Job Seeker Preferences To Improve Job Recomme...

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作者： A. T. Walterbos Delft University of Technology

学位级别：硕士

This thesis focuses on the field of Job Recommendation. Particularly, we focus on using implicit preferences exhibited by the job seeker in interactions with a web platform to propose an improved ranking algorithm for a job recommendation platform called Magnet. me. We also study evaluation of relevance, and evaluation of recommendation sorting algorithms to determine the degree of improvement achieved by the proposed algorithm. Using NDCG with different relevance evaluations, we test performance of the proposed algorithm in an online experiment on the job recommendation platform. We find that the evaluation of relevance strongly affects the distinguishability of NDCG. The evaluation shows that our sorting algorthm outperforms the original algorithm when using classical binary relevance, or relevance evaluations that consider items with negative feedback less relevant than items with missing feedback. However, when using relevance evaluations for NDCG that punish missing feedback more than negative feedback, NDCG loses its capability of distinguishing between algorithm performance. Based on baseline sorting algorithm evaluation MRR and the different evaluations using NDCG, we conclude that the proposed recommendation sorting algorithm outperforms the original algorithm.

关键词： Recommender Systems implicit feedback Ranking sorting algorithm Relevance evaluation NDCG Job Recommendation implicit preferences

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Speech Signals Identification base on Improved DBN

Speech Signals Identification base on Improved DBN

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： CAI Jun YAO Qin ZHANG Yi Chongqing university of posts and telecommunications College of Automation Chongqing university of posts and telecommunications College of Advanced Manufacturing Engineering

For the problem low speech recognition rate, an improved method of combining Deep Belief Network(DBN) with support vector machine(SVM) for analyzing Small sample speech signals is proposed. The speech

ISBN: (纸本)9781467389808

关键词： Speech recognition Deep Belief Network Support Vector Machine Features extraction Feature extraction Support Vector Network Speech recognition Bayesian networks Speech Voice Signal sorting algorithm base on

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A Hybrid Approach to Vietnamese Word Segmentation

A Hybrid Approach to Vietnamese Word Segmentation

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IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF)

作者： Tuan-Phong Nguyen Anh-Cuong Le VNU Univ Engn & Technol Fac Informat Technol 144 Xuan Thuy St Hanoi Vietnam Ton Duc Thang Univ Fac Informat Technol 19 Nguyen Huu Tho StTan Phong WardDist 7 Ho Chi Minh City Vietnam

ISBN: (纸本)9781509041343

Word segmentation is the very first task for Vietnamese language processing. Word-segmented text is the input of almost other NLP tasks. This task faces some challenges due to specific characteristics of the language. As in many other Asian languages such as Japanese, Korean and Chinese, white spaces in Vietnamese are not always used as word separators and a word may contain one or more syllables. In this paper, we propose an efficient hybrid approach to detect word boundary for Vietnamese texts using logistic regression as a binary classifier combining with longest matching algorithm. First, longest matching algorithm is used to catch words that contain more than two syllables in input sentence. Next, the system utilizes the classifier to determine the boundary of 2-syllable words and proper names. Then, the predictions having low confidence conducted by the classifier are verified by a dictionary to get the final result. Our system can achieve an F-measure of 98.82% which is the most accurate result for Vietnamese word segmentation to the best of our knowledge. Moreover, the system also has a high speed. It can run word segmentation for nearly 34k tokens per second.

关键词： Dictionaries White spaces Logistics Particle separators Hidden Markov models Classification algorithms Prediction algorithms White spaces Dictionaries as Topic Prediction algorithms sorting algorithm Hidden Markov models Word Vietnamese Vietnamese Logistics Particle separators Classifiers

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POCAD: a Novel Payload-based One-Class Classifier for Anomaly Detection

POCAD: a Novel Payload-based One-Class Classifier for Anomal...

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3rd National-Foundation-for-Science-and-Technology-Development Conference on Information and Computer Science (NICS)

作者： Xuan Nam Nguyen Dai Tho Nguyen Long Hai Vu Vietnam Natl Univ Univ Engn & Technol Hanoi Vietnam UMI 209 UMMISCO IRD UPMC Paris France IBM Corp TJ Watson Res Ctr Armonk NY 10504 USA

ISBN: (纸本)9781509020980

In this paper, we propose a novel Payload-based One-class Classifier for Anomaly Detection called POCAD, which combines a generalized 2w-gram feature extractor and a one-class SVM classifier to effectively detect network intrusion attacks. We extensively evaluate POCAD with real-world datasets of HTTP-ased attacks. Our experiment results show that POCAD can quickly detect malicious payload and achieves a high detection rate as well as a low false positive rate. The experiment results also show that POCAD outperforms state of the art payload-based detection schemes such as McPAD [4] and PAYL [8].

关键词： Payloads Feature extraction Support vector machines Training Computer science Classification algorithms Computational modeling Payload sorting algorithm computer science Support Vector Network anomaly detection Computational modeling Feature extraction Functional training Classifiers detection rate (DR) Training

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An Online Local Boundary Detection and Classification algorithm for Networked Multi-Robot Systems

An Online Local Boundary Detection and Classification Algori...

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International Conference on Advanced Technologies for Communications (ATC)

作者： Pham Duy Hung Tran Quang Vinh Trung-Dung Ngo Univ Engn & Technol Hanoi Vietnam Univ Brunei Darussalam More Than One Robot Lab Bandar Seri Begawan Brunei Univ Prince Edward Isl Charlottetown PE Canada

ISBN: (纸本)9781509027118

We present an online boundary classification error detection algorithm to improve accuracy of the original distributed boundary detection algorithm for networked multi-robot systems. It is a fully decentralized method based on the geometric approach allowing to suppress boundary errors without recursive process and global synchronization. The accuracy of the ration of correctly identified robots over the total number of robots reaches 100%. We have demonstrated the effectiveness of this boundary detection algorithm in both simulation and real-world environment.

关键词： Robot sensing systems Detection algorithms Nickel Robot kinematics Image edge detection Multi-robot systems multi-robot systems Edge detection Manipulator sensing systems Robot kinematics Detection algorithms boundary detection algorithm sorting algorithm Nickel Robot

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Feature and Weight Selection Using Tabu Search for Improving the Recognition Rate of Duct Anomaly

Feature and Weight Selection Using Tabu Search for Improving...

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2014 IEEE International Conference on Robotics and Biomimetics (ROBIO)

作者： Wang Yongxiong Kai Li Univ Shanghai Sci & Technol Dept Automat Shanghai 200093 Peoples R China

ISBN: (纸本)9781479973972

In real-time anomaly detection problems, reducing the dimensionality and improving recognition rate are two most crucial problems. The unbalanced data distribution is one of main reasons of leading to low recognition rate. In this paper, a hybrid approach using Tabu search (TS) and ensemble classification algorithm is proposed. Tabu search is simultaneously applied to select features and weights of ensemble classification. To relieve unbalanced data problems, three policies are used: taking advantages of the cost function of TS to attach more importance to high recognition rate of minority class in the process of feature selection, constructing new sample sets by using oversampling and undersampling, and using ensemble classification method to improve the detection accuracy at low false positive rates. Experimental results show that the approach is effective to improve the classification accuracy of unbalanced class.

关键词： tabu search Feature extraction Recognition (Psychology) Cost functions Undersampling sorting algorithm data distribution Oversampling Classification Methods duct TBXAS1 gene CACNA1C gene

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Demonstrační program metod řazení v jazyce C

Demonstrační program metod řazení v jazyce C

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作者： Pernica, Lukáš Brno University of Technology

V oboru informačních technologií je jednou ze základních dovedností každého programátora zvládnutí problematiky řadicích algoritmů. Řadicí algoritmy jsou vyu... 详细信息

V oboru informačních technologií je jednou ze základních dovedností každého programátora zvládnutí problematiky řadicích algoritmů. Řadicí algoritmy jsou využívány ve velmi širokém rozmezí a i když se v každém programovacím jazyce zapisují odlišně, jejich princip zůstává stejný. V této práci se budu zabývat problematikou řadicích algoritmů a popisem programu, který je součástí této bakalářské práce. Program má jednoduchou formou demonstrovat principy nejpoužívanějších řadicích algoritmů a slouží tak jako pomůcka pro snazší pochopení metod řazení.

关键词： Řadicí algoritmus demonstrační program Binary Insert sort Bubble sort Select sort Heap sort Shell sort Quick sort Merge sort rozděl a panuj WIN API grafické prostředí sorting algorithm demonstrational program Binary Insert sort Bubble sort

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