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 20 for “"naive Bayes classifier"”.
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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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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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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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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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Identifying lesions in paediatric epilepsy using morphometric and textural analysis of magnetic resonance images
… techniques were considered. The 2-Step Naive Bayes classifier was found to produce 100% subjectwise specificity and 94% subjectwise sensitivity (with 75% lesional specificity, 63% lesional sensitivity). Thus it correctly rejected 13/13 healthy subjects and colocalized lesions in 29/31 of …
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A Comparison of Case-Based Reasoning and Probabilistic Graphical Models in the Context of Learning from Observation
… for future improvement. We show that the Naive Bayes Classifier is better than a previously used PGM model in learning behavior in a vacuum cleaner domain and introduce a state-based retrieval technique in CBR and show that there is no once-size-fits-all approach to learn state-based …
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A comparative analysis of machine learning algorithms for genome wide association studies
… Recursive Partitioning, Logistic Regression and Naive Bayes Classifier. The classification accuracy of these algorithms is calculated in terms of area under the receiver operating characteristic curve (AUC). Conclusively, the logistic regression model with binary classification seems to be the …
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News and financial market
… existing prediction algorithms that are based on Naive Bayes Classifier and Adjusted Document Frequency-Inverse Document Frequency(ADFIDF) weighting. Although occurrence of features selected by ADFIDF weighting can usually represent volatility bursts in financial market, it has been unclear …
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Machine learning in astronomy
… to train, optimise and test a Minimum Error Classifier (MEC), a naive Bayes classifier, a k-Nearest Neighbours (kNN) algorithm, a Support Vector Machine (SVM) and the SkyNet artificial neural network.
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Machine Learning for Radio Frequency Interference Flagging
… RFI using specific machine learning algorithms; Naive Bayes Classifier, K-Nearest Neighbours Classifier, Random Forest Classifier, the U-Net convolution neural network and the Multilayer Perceptron. These algorithms are trained on real data, in which the ground truth includes inherent false …
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Activity recognition with end-user sensor installation in the home
… for recognizing activities that extends the naive Bayes classifier to incorporate low-order temporal relationships was created. Unlike prior work, the system was deployed in multiple residential environments with non-researcher occupants. Preliminary results show that it is possible to …
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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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Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge
… to limit false-positive predictions. Finally, a naive Bayes classifier is used to predict new edges. The Beacon inference engine predicts new edges with a recall rate 77.6% and precision 81.4%. 24% of the total predicted edges are new i.e., they are not present in the prior knowledge.
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Investigating pre-touch sensing to predict grip success in compliant grippers using machine learning techniques
… vector machines, multi-layer perceptrons and a naive Bayes classifier. The various sensor configuration-machine learning combinations were tested and evaluated based on their ability to predict grip success. Additional training was conducted to demonstrate the ability to differentiate fruit from …
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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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Semantic Based Content Search and Content Summarization
… to outperform other statistical summarizers as Naive Bayes Classifier (NEC) and Language Models (LM); the development of a supervised statistical summarization algorithm based on document classification techniques (Text Classification Assisted Summarization for Greek Language-TCASGL); and the …
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A neuro-genetic hybrid approach to automatic identification of plant leaves
… to time and increased the accuracy of the classifier used. The algebraic nature of the GA’s fitness function ensures good performance of the GA. Furthermore, GA was also used to optimize the parameters of a CNN (CNN for image segmentation) and then uniquely combined with PNN to improve and …
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The evolution of online asexual discourse
… the Asexual-other corpus. Using a multinomial Naive Bayes classifier, I found moderate distinguishability between the AVEN-main and non-asexual corpura at the level of individual posts when only considering individual words. To rule out the possibility that the classifier was distinguishing …
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Image Classification using Gabor Filters and Machine Learning
… two additional classification methods based on naive Bayes’ and support vector machine classifiers. Mutual information is used for reducing redundant Gabor features not carrying sufficient object information. Extensive experimentation using real aerial imagery of the Peruvian Andes shows that …
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Variant Detection Using Next Generation Sequencing Data
… improve SNP calling results, we propose a Na¿¿ve Bayes based approach, which combines prior information of known polymorphic sites and population specific allele frequencies with SNP calling results from multiple programs to obtain more accurate SNP genotypes. Results show that our approach has …