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检索条件"主题词=classification algorithm"

共 546 条记录，以下是31-40 订阅

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A Hybrid classification algorithm Approach for Breast Cancer Diagnosis

A Hybrid Classification Algorithm Approach for Breast Cancer...

引用

IEEE Conference on Industrial Electronics and Applications

作者： Abed, Baraa M. Shaker, Khalid Jalab, Hamid A. Shaker, Hothefa Mansoor, Ali Mohammed Alwan, Ahmad F. Al-Gburi, Ihsan Salman Univ Anbar Coll Comp Sci & Informat Technol Ramadi Iraq Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur Malaysia Modern Coll Business & Sci Muscat Oman Univ Nizwa Coll Arts & Sci Dept Math & Phys Sci Nizwa Oman Istanbul Kemerburgaz Univ Grad Sch Sci & Engn Istanbul Turkey

ISBN: (纸本)9781509009251

Early diagnosis of Breast Cancer is significantly important to treat the disease easily therefore it is necessary to develop techniques that can help physicians to get accurate diagnosis. This study suggests a hybrid classification algorithm which is based upon Genetic algorithm (GA) and k Nearest neighbor algorithm (kNN). GA algorithm has been used for its primary purpose as an optimization technique for kNN by selecting best features as well as optimization of the k value, while the kNN is used for classification purpose. The planned algorithm is tested by applying it on Wisconsin Breast Cancer Dataset from UCI Repository of Machine Learning Databases using different datasets in which the first is Wisconsin Breast Cancer Database (WBCD) and the second one is Wisconsin Diagnosis Breast Cancer (WDBC) which has changes in the number of attributes and number of instances. The proposed algorithm was measured against different classifier algorithms on the same database. The evaluation results of the algorithm proposed have achieved 99% accuracy.

关键词： Breast Cancer Diagnosis classification algorithm Genetic algorithm and k Nearest Neighbor algorithm

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New classification algorithm for electromyography-based computer cursor control system

New classification algorithm for electromyography-based comp...

引用

IEEE SoutheastCon 2005

作者： Chin, C Barreto, A Zhai, J Li, C Florida Int Univ Dept Elect & Comp Engn Miami FL 33199 USA

ISBN: (纸本)0780388658

At present, a three-input Electromyography (EMG) system has been created to provide real-time, hands-free cursor control. The system uses the real-time spectral analysis of three EMG signals to produce the following five cursor actions: i) LEFT, ii) RIGHT, iii) UP, iv) DOWN, v) LEFT-CLICK. The three EMG signals are obtained from two surface electrodes placed on the left and right temples of the head and one electrode placed in the forehead region. The present system for translating EMG activity into cursor actions does not always discriminate between up and down EMG activity efficiently. To resolve this problem it was proposed that the three-electrode system be converted into a four-electrode system, using two electrodes in the forehead of the user, instead of one. This paper compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance.

关键词： keyboards mouse controllers (computers) electromyography signal classification spectral analysis handicapped aids human computer interaction classification algorithm electromyography-based computer cursor control system three-input electromyography system EMG real-time hands-free cursor control real-time spectral analysis EMG signals cursor actions cursor left motion cursor right motion cursor up motion cursor down motion cursor left-click surface electrodes forehead region temple electrodes EMG activity translation activity discrimination four-electrode system Matlab simulations classification performance

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A classification algorithm for high-dimensional data

A classification algorithm for high-dimensional data

引用

INNS Conference on Big Data

作者： Roy, Asim Arizona State Univ Dept Informat Syst Tempe AZ 85281 USA

With the advent of high-dimensional stored big data and streaming data, suddenly machine learning on a very large scale has become a critical need. Such machine learning should be extremely fast, should scale up easily with volume and dimension, should be able to learn from streaming data, should automatically perform dimension reduction for high-dimensional data, and should be deployable on hardware. Neural networks are well positioned to address these challenges of large scale machine learning. In this paper, we present a method that can effectively handle large scale, high-dimensional data. It is an online method that can be used for both streaming and large volumes of stored big data. It primarily uses Kohonen nets, although only a few selected neurons (nodes) from multiple Kohonen nets are actually retained in the end;we discard all Kohonen nets after training. We use Kohonen nets both for dimensionality reduction through feature selection and for building an ensemble of classifiers using single Kohonen neurons. The method is meant to exploit massive parallelism and should be easily deployable on hardware that implements Kohonen nets. Some initial computational results are presented.

关键词： Kohonen nets classification algorithm online learning feature selection high-dimensional data

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De-Word classification algorithm Based on the Electric Power of Large Data Library Retrieval 2

De-Word Classification Algorithm Based on the Electric Power...

引用

2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network (UCAWSN)

作者： Guo, Xiaoli Sun, Huiyu Wang, Ling Qu, Zhaoyang Ding, Wei Northeast Dianli Univ Chuanying 132012 Jilin Peoples R China

ISBN: (纸本)9789401796187;9789401796170

In order to improve the performance of text classification and information retrieval in big data of electric power domain, we propose a novel Chinese language classification algorithm-De-word classification algorithm. Focusing on the key role played by the De-word in modern Chinese language, this algorithm examines Chinese text classification method from a unique angle. Besides, on the basis of traditional weighted algorithm, it designs a novel relevance weighting model-De-TFIDF, and achieves a higher correlation in text information retrieval. Experiments show that, De-word classification algorithm significantly improves the efficiency of text classification, significantly improved information retrieval performance.

关键词： Big data classification algorithm De-word Relevance

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A classification algorithm for Water Environment Health Risk Assessment based on Unascertained Mathematics and Its Application 4

A Classification Algorithm for Water Environment Health Risk...

引用

IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Wei, Yiming Dong, Zengchuan Xu, Wei Li, Dayong Zhang, Fangyu Hohai Univ Coll Hydrol & Water Resources Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538653739

To solve the unascertainty in water environmental risk assessment, a classification algorithm that based on unascertained mathematics is established is proposed. And the unascertained information of pollutant concentration in water environment systems, population health life and body weight are considered in the algorithm. Among it, ammonia nitrogen (NH3N) and arsenic (As) are selected as a non-carcinogenic chemical indicator and a chemical carcinogen index respectively. Then the risk degree and risk index can be calculated separately according to the proposed risk level classifications. The case study in Taoge River System shows that the proposed algorithm is capable of evaluating the health risk level in water environment and could provide useful information for the regional water environmental management.

关键词： water environment health risk unascertained mathematics classification algorithm risk index

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Directional Folded Antenna for Brain Stroke Detection Based on classification algorithm 4

Directional Folded Antenna for Brain Stroke Detection Based ...

引用

IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Wu, Yizhi Pan, Deng Donghua Univ Coll Informat Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9781538653739

To meet the demands on wideband unidirectional antennas in distinguishing ICH and IS stroke based on classification algorithm, a novel folded antenna is presented. The design of the antenna starts with a planar diplo antenna with bridge-shape ground. Then some slots are added to the ground to expand the bandwidth. Next, a folding technology is applied to the monopole to enhance its directivity while the overall size is reduced markedly at the same time. At last, a reflector and a pair of top-facing p-shape parasitic patches are applied to the antenna to increase the gain and decrease the voltage standing wave ratio (VSWR) at 1.7GHz. The final designed antenna has a dimensions of 0.293 lambda x0.107 lambda x0.053. (lambda is the wavelength at the lowest operating frequency). It has a measured reflection coefficient less than -10dB fractional bandwidth of 76% (1.1-2.45 GHz) and a peak gain of 4.5 dBi. In order to validate the effectiveness of the proposed antenna in the application, the proposed folded antenna is simulated with the human brain model and the result is classified by PCA and LDA classification algorithms. Finally, the accuracy of the final classification result is 100%, which indicates that the proposed folded antenna can be well applied to the brain stroke detection system.

关键词： folded antenna classification algorithm stroke microwave detection

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Research on classification algorithm of News Pages Based on Domain Ontology

Research on Classification Algorithm of News Pages Based on ...

引用

2nd International Conference on Measurement, Instrumentation and Automation (ICMIA 2013)

作者： Xie, Caiyun Hu, Xiaorong Nanchang Teachers Coll Dept Informat Sci Nanchang Peoples R China

ISBN: (纸本)9783037857519

This paper proposes the classification algorithm of news pages based on domain Ontology. In order to improve the shortage of current classification algorithm that only considers the content similarity, this paper presents the semantic classification method which considers both content similarity and structural correlation. Firstly, it parses the Ontology to get Ontology category vector, extracts keywords of news pages' texts and drops semantic dimension. At this time, finding out the same vocabulary and ontology category vector in page texts to constitute the text expectation vector, and then calculating the content similarity between ontology category vector and expectation vector of text by using the law of cosines. Secondly, the common vocabularies are mapped to the ontology hierarchy chart, and the structural relevancy is obtained by calculating weighted path of this directed acyclic graph. Finally, it calculates the correlation degree of the news pages and Ontology by combining both, and determines the category of news pages by judging the size relationship between the result and the initial threshold value.

关键词： classification algorithm Ontology Integrated Correlation Degree

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OCEC: A novel classification algorithm based on evolutionary computation 6

OCEC: A novel classification algorithm based on evolutionary...

引用

6th International Conference on Signal Processing

作者： Liu, J Zhong, WC Liu, F Jiao, LC Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China

A novel classification algorithm, OCEC, based on evolutionary computation for data mining is proposed. It is compared to GA-based and non GA-based algorithms on 8 datasets from the UCI machine learning repository. Res... 详细信息

ISBN: (纸本)0780374886

关键词： classification data mining evolutionary computation learning (artificial intelligence) classification algorithm evolutionary computation organizational coevolutionary algorithm data mining UCI machine learning repository prediction accuracy

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A Microblog classification algorithm for Real-time Search

A Microblog Classification Algorithm for Real-time Search

引用

2nd International Conference on Information Technology and Management Innovation (ICITMI 2013)

作者： Yuan, Jingbo Wang, Bairong Yang, Jihao Ding, Shunli Northeastern Univ Qinhuangdao Peoples R China Northeastern Univ Sch Business Adm Qinhuangdao Peoples R China Northeastern Univ Coll Informat Sci & Engn Qinhuangdao Peoples R China Environm Management Coll Beijing Peoples R China

ISBN: (纸本)9783037858646

As a social network, microblog has obtained great attention and gotten wide application. Applications of microblog need to retrieve quickly information with the support of real-time search technology in order to implement information sharing. A query classification algorithm of microblog for real-time search was put forward. Based on question classification mechanism, the algorithm divides queries into two categories: the candidate queries and the popular queries, and takes separate storage strategy. Test results show that the classification algorithm can reduce real-time search time and improve the efficiency of retrieval.

关键词： social network real-time search technology microblog classification algorithm

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English Language Statistical Machine Translation Oriented classification algorithm

English Language Statistical Machine Translation Oriented Cl...

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International Conference on Intelligent Transportation, Big Data and Smart City (ICITBS)

作者： Yan, Jia Chao, Wang Mudanjiang Normal Univ Heilongjiang 157011 Mudanjiang Peoples R China

ISBN: (纸本)9781509004645

In this paper, we study on the problem of statistical machine translation (SMT) for English language, and the main innovation is that we introduce the SVM classifier to solve this problem. Particularly, the process of statistical machine translation is constructed of two modules, that is, 1) constructing the target language sentence, and 2) translating from target texts to source texts language. Afterwards, framework of the statistical machine translation system is provided. The main idea of statistical machine translation is in that the sentence with highest probability is selected by optimizing an objective function, which describes the relationships between source language sentences and target language sentences. Finally, experimental results demonstrate that our proposed algorithm outperforms Topic-Based SMT and Rule Based SMT.

关键词： Statistical machine translation classification algorithm English translation SVM Objective function

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