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检索条件"主题词=Naive bayes algorithm"

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naive bayes Classifiers for Music Emotion Classification Based on Lyrics 16

Naive Bayes Classifiers for Music Emotion Classification Bas...

引用

16th IEEE/ACIS International Conference on Computer and Information Science (ICIS)

作者： An, Yunjing Sun, Shutao Wang, Shujuan Commun Univ China Informat Engn Sch Beijing 100024 Peoples R China Minist Culture Key Lab Acoust Visual Technol & Intelligent Contr Beijing 100024 Peoples R China Beijing Key Lab Modern Entertainment Technol Beijing 100024 Peoples R China

ISBN: (纸本)9781509055074

There is a constantly growing interest in evaluating music information retrieval (MIR) systems that can provide effective management of the music resources. The crucial characteristic of music is its emotion, which reflect the human's perception. To do the automatic classification of Chinese music emotions more effective, we use the lyrics of music to analysis and classify music based on emotion. There are many algorithms to achieve text classification, and one of the most popular algorithms is naive bayes algorithm. Although it is simple, it can classify text effectively. In this paper, we crawl the music lyrics and their labels from a popular website named Baidu music and make our four different datasets. We also train four classifiers with different datasets and report their performance. We evaluate the classifiers trained by four different datasets, and the final accuracy we get is approximately 68%.

关键词： naive bayes algorithm music emotion lyrics

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FOREIGN RATE EXCHANGE PREDICTION USING NEURAL NETWORK AND SENTIMENT ANALYSIS

FOREIGN RATE EXCHANGE PREDICTION USING NEURAL NETWORK AND SE...

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International Conference on Advances in Computing, Communication Control and Networking

作者： Swagat Ranjit Shruti Shrestha Sital Subedi Subama Shakya Department of Electronics and Computer Engineering Tribhuvan University Lalitpur Nepal

ISBN: (纸本)9781538641200

Foreign currency exchange plays a vital role for currency trading in the financial market. To manage large volume of transactions in modern world, it requires support from the computer algorithms. There could be potential problems like trading without a plan, having unrealistic expectation, failing to adapt to the market and many more. This paper examines on foreign exchange market prediction using neural network and sentiment analysis. There are various techniques and algorithms for prediction but different algorithms have different accuracy. Among them, one of the best and accurate method is Artificial Neural Network (ANN). Neural network parameters consist of number of neurons, use of bias neurons, number of hidden layers, activation functions and training methods. Root Mean Squared Error (RMSE) was found to be 0.0034 with 6 hidden nodes using ANN. As the price movement is also directly proportional to market sentiment, we applied sentiment analysis using combination of naive bayes and lexicon based algorithm to analyze the opinion of different traders and predict the overall sentiment. Sentiments are taken from tweets and were classified as positive or negative. In sentiment analysis, accuracy was found to be 90.625%.

关键词： Foreign exchange rate Artificial neural network Sentiment analysis naive bayes algorithm Lexicon based algorithm

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Two Layers Multi-class Detection Method for Network Intrusion Detection System

Two Layers Multi-class Detection Method for Network Intrusio...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Yuan, Yali Huo, Liuwei Hogrefe, Dieter Inst Comp Sci Goldschmidtstr 7 D-37077 Gottingen Germany Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Liaoning Peoples R China

ISBN: (纸本)9781538616291

Intrusion Detection Systems (IDSs) are powerful systems which monitor and analyze events in order to detect signs of security problems and take action to stop intrusions. In this paper, the Two Layers Multi-class Detection (TLMD) method used together with the C5.0 method and the naive bayes algorithm is proposed for adaptive network intrusion detection, which improves the detection rate as well as the false alarm rate. The proposed TLMD algorithm also addresses some difficulties in data mining situations such as handling imbalance datasets, dealing with continuous attributes, and reducing noise in training dataset. We compared the performance of the proposed TLMD method with that of existing algorithms, using the detection rate, accuracy as well as false alarm rate on the KDDcup99 benchmark intrusion detection dataset. The experimental results prove that the proposed TLMD method has a reduced false alarm rate and a good detection rate based on the imbalanced dataset.

关键词： Intrusion Detection Systems C5.0 Method naive bayes algorithm Imbalance Data Detection Rate False Alarm Rate

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A Classification Model to Analyze the Spread and Emerging Trends of the Zika Virus in Twitter 3rd

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3rd International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Tripathy, B. K. Thakur, Saurabh Chowdhury, Rahul VIT Univ Sch Comp Sci & Engn Vellore Tamil Nadu India

ISBN: (纸本)9789811038747;9789811038730

The Zika disease is a 2015-16 virus epidemic and continues to be a global health issue. The recent trend in sharing critical information on social networks such as Twitter has been a motivation for us to propose a classification model that classifies tweets related to Zika and thus enables us to extract helpful insights into the community. In this paper, we try to explain the process of data collection from Twitter, the preprocessing of the data, building a model to fit the data, comparing the accuracy of support vector machines and naive bayes algorithm for text classification and state the reason for the superiority of support vector machine over naive bayes algorithm. Useful analytical tools such as word clouds are also presented in this research work to provide a more sophisticated method to retrieve community support from social networks such as Twitter.

关键词： Zika Twitter analysis Twitter classification Support vector machines naive bayes algorithm

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Design of a Novel Wireless Power System Using Machine Learning Techniques for Drone Applications

Design of a Novel Wireless Power System Using Machine Learni...

引用

IEEE Wireless Power Transfer Conference (WPTC)

作者： Jeong, Soyeon Bito, Jo Tentzeris, Manos M. Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (纸本)9781509045853

In this paper, the design of a novel wireless power transfer system utilizing drones with machine learning techniques is presented. Research on drones is currently a fast growing field with a great potential in many ubiquitous applications. The wireless power transfer system with the fixed operation frequency at 13.56MHz is applied to an 1-coil receiver on the drone, with an array of transmitter coils on the ground. This work presents an approach where the data is considered "classified" using machine learning techniques, which allows the accurate prediction of the drone's position, thus enhancing the wireless power transfer efficiency.

关键词： Wireless power transmission magnetic resonant inductive coupling drones machine learning classification naive bayes algorithm

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Research on Text Mining algorithm Based on Focused Crawler 12

Research on Text Mining Algorithm Based on Focused Crawler

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12th International Conference on Computer Science and Education (ICCSE)

作者： Zhang, Qiusheng Lin, Mingyu Jun, Jianping Zhang, Xingyun Hubei Business Coll Sch Elect & Infounat Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9781509025084

Internet has become the world's largest information repository, especially the explosive growth of the text data on the web, the disadvantages that it need much more time to acquire and update web pages, and is not high precision have become more obvious. The text mining algorithm based on focused crawler is proposed in this paper, it classifies and integrates the whole web pages by topic using topic crawler algorithm as much as possible, which greatly improves the retrieval ability of the web pages, naive bayes algorithm is adopted on this basis, which realizes the text mining processing of the web *** experimental results show that the algorithm has good feasibility and higher recall ratio and precision ratio of the web pages.

关键词： focused crawler naive bayes algorithm text mining association rules

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Two Layers Multi-class Detection Method for Network Intrusion Detection System

Two Layers Multi-class Detection Method for Network Intrusio...

引用

IEEE Symposium on Computers and Communications

作者： Yali Yuan Liuwei Huo Dieter Hogrefe Institute of Computer Science Goettingen Germany School of Computer Science and Engineering Northeastern University Shenyang China

关键词： Intrusion Detection Systems C5.0 Method naive bayes algorithm Imbalance Data Detection Rate False Alarm Rate

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Software Defect Prediction Model Research for Network and Cloud Software Development

Software Defect Prediction Model Research for Network and Cl...

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2017 5th International Conference on Mechatronics,Materials,Chemistry and Computer Engineering(ICMMCCE 2017)

作者： Yejuan Yang Department of Information Engineering Jianghai Polytechnic College

With the process of software development and application basing on network and cloud, the change of software development requires new software defect prediction method for these kinds of software development, which can solve the problems of the traditional software defect prediction method based on target project, such as the same predict background and higher cost of defect tagging. A new software defect prediction method based on multi source data oriented network and cloud development process is proposed. This method selects the predictive candidates from multisource projects which have similar characteristics as objective projects, and then guides the training data selection by the software modules, finishes the prediction based on naive bayesian algorithm. Finally through algorithm experiment this method is proved superior to the traditional WP prediction model.

关键词： Oriented Network and Cloud Development Software Defect Prediction Multi Source Project naive bayes algorithm

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Teacher's Performance Evaluation Tool Using Opinion Mining with Sentiment Analysis

Teacher's Performance Evaluation Tool Using Opinion Mining w...

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IEEE Region 10 Symposium (TENSYMP)

作者： Balahadia, Francis F. Fernando, Ma. Corazon G. Juanatas, Irish C. FEU Inst Technol Coll Comp Studies Manila Philippines

ISBN: (纸本)9781509009312

The research aims to develop a teacher's performance evaluation tool using opinion mining with sentiment analysis. The study may help to identify the strengths and weaknesses of the faculty members based on the positive and negative feedback of the students either in English or in Filipino language. The proposed system provides the sentiment score from the qualitative data and numerical response rating from the quantitative data of teachers evaluation. It will also graphically represent the evaluation result including the percentage of positive and negative feedback of the students. Thus, the school administrators and educators will be more aware about the sentiments and concerns of the students.

关键词： Sentiment Analysis naive bayes algorithm Teacher Performance Rating Quantitative and Qualitative Ratings

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A SURVEY ON CLASSIFICATION TECHNIQUES FOR TEXT MINING 3

A SURVEY ON CLASSIFICATION TECHNIQUES FOR TEXT MINING

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3rd International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Brindha, S. Sukumaran, S. Prabha, K. Erode Arts & Sci Coll Dept Comp Sci Erode Tamil Nadu India Periyar Univ PG Extens Ctr Comp Sci Dharmapuri Tamil Nadu India

ISBN: (纸本)9781467392068

The development of the World Wide Web it is no longer feasible for a user can understand all the data coming from classify into categories. The expansion of information and power automatic classification of data and textual data gains increasingly and give high performance. In this paper five important text classifications are described naive bayesian, K-Nearest Neighbour, Support Vector Machine, Decision Tree and Regression. Which are categorized the text data into pre define class. The target of the paper is to study different classification techniques and finding the classification accuracy for different datasets. An efficient and effective text documents into mutually exclusive categories.

关键词： K-Nearest Neighbour naive bayes algorithm Support Vector Machine Decision Tree Methods Log Regression

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