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1.
Predicting Substantiation of Office of Inspector General Investigations Using Multinomial Naïve Bayes and Natural Language Processing
by Starr, Alexis V., D.Engr.  The George Washington University. 2021: 119 pages; 28256297.
2.
Application of a Hidden Bayes Naïve Multiclass Classifier in Network Intrusion Detection
by Koc, Levent, Ph.D.  The George Washington University. 2013: 146 pages; 3546303.
6.
Clustering algorithms for next-generation sequencing data from heterogenous populations
by Prabhakara, Shruthi, Ph.D.  The Pennsylvania State University. 2012: 126 pages; 3737327.
7.
Advances in online learning-based spam filtering
by Sculley, D., Ph.D.  Tufts University. 2008: 212 pages; 3320103.
8.
Ancestry Informative Markers Tailored to Hispanic Populations
by Setser, Casandra Hernandez, Ph.D.  University of North Texas Health Science Center at Fort Worth. 2020: 97 pages; 27837053.
9.
Structural induction: Towards automatic ontology elicitation
by Silvescu, Adrian, Ph.D.  Iowa State University. 2008: 187 pages; 3307040.
10.
An efficient approach to machine learning based text classification through distributed computing
by Immaneni, Raghu Nandan, M.S.  California State University, Long Beach. 2015: 86 pages; 1603338.
12.
Latent Variable Modeling for Networks and Text: Algorithms, Models and Evaluation Techniques
by Foulds, James Richard, Ph.D.  University of California, Irvine. 2014: 287 pages; 3631094.
14.
A Multinomial Theorem for Formal Power Series under Composition
by Monkam, Galamo F., Ph.D.  Morgan State University. 2020: 85 pages; 28152648.
15.
Examining Economic Redevelopment Programs with Multinomial Logistic Regression in Colorado and Ohio
by Tharp, Kelsey, M.S.  Southern Illinois University at Edwardsville. 2015: 90 pages; 10000369.
16.
Modeling content lifespan in Online Social Networks using data mining
by Gibbons, John, Ph.D.  University of Kansas. 2014: 111 pages; 3625219.
17.
Detection and explanation of statistical differences across a pair of groups
by Sverchkov, Yuriy, Ph.D.  University of Pittsburgh. 2014: 159 pages; 3647988.
18.
Hierarchical Bayes estimation and empirical best prediction of small-area proportions
by Liu, Benmei, Ph.D.  University of Maryland, College Park. 2009: 223 pages; 3359401.
19.
Benchmarks for Evaluating Anomaly-Based Intrusion Detection Solutions
by Miller, Nicholas J., M.S.  California State University, Long Beach. 2018: 30 pages; 10752128.
20.
Feature selection techniques and applications in bioinformatics
by Dittman, David, M.S.  Florida Atlantic University. 2011: 147 pages; 1504155.
21.
Cyber-based behavioral modeling
by Robinson, David John, Ph.D.  Dartmouth College. 2010: 225 pages; 3426407.
22.
Networks of mixture blocks for non parametric Bayesian models with applications
by Porteous, Ian, Ph.D.  University of California, Irvine. 2010: 123 pages; 3403449.
23.
Nonparametric Bayes: Inference under nonignorable missingness and model selection
by Linero, Antonio, Ph.D.  University of Florida. 2015: 147 pages; 10299009.
25.
In-Node Vehicle Classification and Identification
by Bavkar, Indraneel N., M.S.  California State University, Long Beach. 2017: 50 pages; 10639676.
26.
Needle in the Noise: Detecting Public Safety Events Over Twitter
by Paulson, Keith, M.Eng.  University of Colorado Colorado Springs. 2019: 52 pages; 13864461.
27.
A methodology for risk assessment of product line architectures
by Jalali, Amir H., M.S.  West Virginia University. 2008: 138 pages; 1458740.
28.
Classifying Websites Using Word Vectors and Other Techniques: An Application of Zipf’s Law
by Robles, Alejandro, M.S.  California State University, Long Beach. 2019: 50 pages; 22589849.
29.
Essays in the Dynamics Bayesian Models in Marketing
by Kim, Bumsoo, Ph.D.  The George Washington University. 2013: 100 pages; 3591693.
30.
Predicting National Basketball Association Game Outcomes Using Ensemble Learning Techniques
by Valenzuela, Russell, M.S.  California State University, Long Beach. 2018: 54 pages; 10980443.
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