Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 74 for “"Naive Bayes"”.
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Clustered Naive Bayes
… In this thesis, I present the Clustered Naive Bayes classifier, a hierarchical extension of the classic Naive Bayes classifier that ties several distinct Naive Bayes classifiers by placing a Dirichlet Process prior over their parameters. A priori, the model assumes that there exists a …
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Masquerade detection using fortified naive Bayes
… Roy Maxion and Kevin Killourhy utilized a Naive Bayes classifier for detection using enriched Unix command lines, which are command line entries that still contain flags and other data. They discovered a problem with users that they dubbed supermasqueraders. These were users that would …
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Improving multi-class text classification with Naive Bayes
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
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Ontology-based annotation using naive Bayes and decision trees
… and model the annotations with a group of naive Bayes classifiers, then explore the inherent relationship among different components defined by the ontology using a probabilistic decision tree model. Our solution outperforms conventional text mining approaches by taking advantage of an …
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An Evaluation of Text Classification Methods for Literary Study
… previous results, such as SVM does not beat naive Bayes in both cases. Some findings are new to this area---SVM and naive Bayes select top features in different frequency ranges; stemming might harm feature selection methods. These experiment results provide new insights to the relation …
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SVMAUD: Using textual information to predict the audience level of written works using support vector machines
… machine learning methods, including cosine, Naive Bayes, and Support Vector Machines (SVM), can suggest the grade level of an essay based on the vocabulary chosen by the author. The audience level prediction and essay grading problems share the same inputs, expert-labeled documents, and …
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Machine learning on Web documents
… vector machine and the fast but inaccurate Naive Bayes, to make them more effective for the Web. The support vector machine, which cannot currently handle the large amount of Web data potentially available, is sped up by "bundling" the classifier inputs to reduce the input size. The Naive …
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Identifying users on social networking using pattern recognition in messages
… recognition with the aid of an extension of the Naive Bayes method called the Friendship Naive Bayes. Since specific patterns could be observed by examining the communication history between users, the proposed scheme uses these patterns to authenticate that the new message was written by the …
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Um assistente de feedback para o serviço de filtragem do software direto
… os conceitos gerais de probabilidades, redes Bayesianas e classificadores. Procura-se descrever as características gerais dos classificadores, em especial o Naive Bayes, sua lógica e seu desempenho comparado a outros classificadores. São abordados, também, conceitos relacionados ao modelo de …
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A standards-based grading model to predict students' success in a first-year engineering course
… the number of variables used in each model. The Naive Bayes Classifier and an Ensemble model using a combination of models (i.e., Support Vector Machine, K-Nearest Neighbors, and Naive Bayes Classifier) had the best results among the seven tested models. This study identified possible threshold …
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Leveraging Machine Learning and Causal Inference for Loan Default Prediction
… such as Logistic Regression, Random Forest, Naive Bayes, XGBoost, and CatBoost final classification. For performance validation, the modeling pipelines (feature selection + prediction) were evaluated for accuracy, precision, recall, and F1-score to determine their effectiveness in predicting …
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Constructing a web application for identification, detection and analysis of pattern based fraud
… purchases of online products and using a Naive Bayes algorithm to be able to detect an flag the suspicious such. The algorithms selection is based on the dataset size (small dataset, since credit card details include sensitive data) and due to the high probability performance of Naive …
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Análisis de la Encuesta de Salud Nacional y Examen de Nutrición de Estados Unidos (NHANES) usando machine learning
… AdaBoost Classifier, Random Forest Classifier, Naive Bayes, Logistic Regression y k-NN de la librería sklearn. El mejor modelo se obtiene con AdaBoost y una exactitud de 76.33, aunque el Naive Bayes ofrece un buen resultado del TPR de 62.69 al obtenerse la menor cantidad de falsos negativos …
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Topic Identification from Spoken TED-Talks
… na lineárnu klasifikáciu, konkrétne Multinomial Naive Bayes a Linear Support Vector Machines, kde druhá technika dosiahla vyššiu presnosť klasifikácie.
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Development of an autonomous distributed multiagent monitoring system for the automatic classification of end users
… Oracle data mining classification algorithms: Naive Bayes, Adaptive Naive Bayes, Decision Trees, and Support Vector Machine were utilized to analyse the results from the data gathering process in order to automate the classification of excel spreadsheet developers. The accuracy of the …
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Desarrollo de un modelo predictivo mediante Machine Learning para la evolución de la función renal después de cirugía cardíaca
… Trees, Gradient Boosting, AdaBoost y Gaussian Naive Bayes. El modelo con mejor rendimiento fue Gaussian Naive Bayes, que alcanzó un área bajo la curva ROC (AUC) de 0.669 y una sensibilidad del 78.2%, aunque con una elevada tasa de falsos positivos. También se evaluaron diferentes técnicas de …
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A Comparative Study on Feature Extraction and Classification/Clustering of Fake News and Conspiracy Theories from Twitter Data
… to the other algorithms i.e. multinomial naive bayes, logistic regression and decision tree. The Bag of Words model yields an accuracy of 52.3% for both multinomial naive bayes and logistic regression algorithms and a lower range of accuracies for the other two algorithms i.e. svm and …
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Element Detection in Japanese Comic Book Panels
… uses machine learning algorithms. Specifically, Naive Bayes, Maximum Entropy, and support vector machine are used to detect speech bubbles. The algorithms are trained in a fully-supervised way and a semi-supervised way. Both the expert system and the machine learning system achieved high …
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Automatic Document Classification in Small Environments
… with better results than the traditional Naive Bayes implementation of classification.</p>
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Incremental learning algorithm for anomaly detection applied to computed tomography scans in nuclear industry
… approaches have employed ML techniques such as Naive Bayes or proximity measures such as nearest neighbors on numeric 1D datasets and for intrusion detection. In this research, a new soft thresholding-based algorithm that can enhance model prediction in existing IL frameworks and ensure stable …
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