Digital Commons Network^™

Containing Compounding Container Congestion, Curtis Salinger

CMC Senior Theses

The Covid-19 pandemic caused major disruptions throughout the container shipping supply chain. Professor Dongping Song of Liverpool University wrote a paper discussing the logistical vulnerabilities in the supply chain, including the issue of congestion in ports. This paper examines the Port of Los Angeles from 2018-2021 as it relates to Song’s paper to see how its operations were impacted during the Covid-19 timeframe. It is found that labor shortages, chassis shortages, and change in trade behavior each contributed to the congestion. Unfortunately, the implemented policies were insufficient to bolster the port against sustained challenges and congestion continues to worsen.

Reducing Print Time While Minimizing Loss In Mechanical Properties In Consumer Fdm Parts, Long Le, Mitchel A. Rabsatt, Hamid Eisazadeh, Mona Torabizadeh

Mechanical & Aerospace Engineering Faculty Publications

Fused deposition modeling (FDM), one of various additive manufacturing (AM) technologies, offers a useful and accessible tool for prototyping and manufacturing small volume functional parts. Polylactic acid (PLA) is among the commonly used materials for this process. This study explores the mechanical properties and print time of additively manufactured PLA with consideration to various process parameters. The objective of this study is to optimize the process parameters for the fastest print time possible while minimizing the loss in ultimate strength. Design of experiments (DOE) was employed using a split-plot design with five factors. Analysis of variance (ANOVA) was employed to …

Review Of Copula For Bivariate Distributions Of Zero-Inflated Count Time Series Data, Dimuthu Fernando, Mohammed Alqawba, Manar Samad, Norou Diawara

Mathematics & Statistics Faculty Publications

The class of bivariate integer-valued time series models, described via copula theory, is gaining popularity in the literature because of applications in health sciences, engineering, financial management and more. Each time series follows a Markov chain with the serial dependence captured using copula-based distribution functions from the Poisson and the zero-inflated Poisson margins. The copula theory is again used to capture the dependence between the two series.

However, the efficiency and adaptability of the copula are being challenged because of the discrete nature of data and also in the case of zero-inflation of count time series. Likelihood-based inference is used …

Methods Of Anomaly Detection: An Applied Framework And Application To Health Economics, Nathaniel Eric Islip

EWU Masters Thesis Collection

No abstract provided.

การปรับปรุงความสามารถในการพยากรณ์แบบไบนารี่โดยใช้การเรียนรู้เมตาแบบถ่วงน้ำหนักแบบปรับสำหรับการจำแนกความยากจนระดับครัวเรือนในประเทศไทย, ธารินทร์ สุขเนาว์

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้มีวัตถุประสงค์เพื่อศึกษาปัจจัยที่มีความสัมพันธ์กับความยากจนในระดับครัวเรือนและเสนอวิธีการเปรียบเทียบและปรับปรุงความสามารถในการพยากรณ์แบบไบนารี่โดยใช้การเรียนรู้เมตาแบบถ่วงน้ำหนักแบบปรับจากการคำนวนค่าถ่วงน้ำหนักวิธีที่ดีที่สุดสำหรับการจำแนกความยากจนระดับครัวเรือนในประเทศไทย โดยนำเสนอวิธีการสองขั้นตอน คือนำตัววัดประสิทธิภาพการทำนายมาใช้ในการคำนวณค่าถ่วงน้ำหนักแบบปรับ ซึ่งนำมาใช้เสมือนเป็นค่าถ่วงน้ำหนักเริ่มต้นที่ให้กับแต่ละตัวแบบ จากนั้นจึงทำนายผลด้วยวิธีการวิเคราะห์การถดถอยลอจิสติกอีกขั้นตอนหนึ่ง งานวิจัยนี้ศึกษาการคำนวณค่าถ่วงน้ำหนักแบบปรับจากตัววัดประสิทธิภาพการทำนายใน 3 กรณี ได้แก่ 1. การใช้ค่า AUC 2. การใช้ค่า F1-Score โดยพิจารณาจุดตัด 0.5 และ 3. การใช้ค่า F1-Score โดยพิจารณาค่าจุดตัดที่เหมาะสมที่สุดจากดัชนีโยเดนที่สูงสุด นอกจากนี้ เนื่องจากชุดข้อมูลสำรวจประชากรรายครัวเรือนในระดับพื้นที่มีความไม่สมดุลของระดับความยากจน จึงใช้เทคนิค SMOTE ในการจัดการกับข้อมูลที่ไม่สมดุล ทั้งนี้ ผู้วิจัยได้ทำการเปรียบเทียบผลลัพธ์จากชุดข้อมูลก่อนและหลังใช้เทคนิค SMOTE ผลการศึกษาพบว่า ปัจจัยที่มีความสัมพันธ์กับความยากจนในระดับครัวเรือนสูงมีหลายปัจจัย อาทิ อายุของหัวหน้าครัวเรือน จำนวนผู้ที่ได้รับบัตรสวัสดิการแห่งรัฐในครัวเรือน,ค่าใช้จ่ายเพื่อการบริโภคในครัวเรือน เป็นต้น และวิธีการคำนวณค่าถ่วงน้ำหนักแบบปรับจากตัววัดประสิทธิภาพ F1-Score ที่จุดตัด 0.5 มีประสิทธิภาพสูงสุดจากการพิจารณาด้วยค่าความแม่นยำในชุดข้อมูลตั้งต้นก่อนใช้เทคนิค SMOTE อย่างไรก็ตาม จากการทดสอบในชุดข้อมูลที่มีการจัดการกับข้อมูลที่ไม่สมดุลด้วยวิธี SMOTE พบว่า ประสิทธิภาพในการทำนายไม่ปรากฏว่าวิธีการคำนวณค่าถ่วงน้ำหนักแบบปรับจากตัววัดประสิทธิภาพแบบใดแบบหนึ่งที่มีประสิทธิภาพสูงสุดอย่างชัดเจน

Comparison Of Caregiver- And Child-Reported Quality Of Life In Children With Sleep-Disordered Breathing, Phoebe Kuo Yu, Kaitlyn Cook, Jiayan Liu, Raouf S. Amin, Craig Derkay, Lisa M. Elden, Susan L. Garetz, Alisha S. George, Sally Ibrahim, Stacey L. Ishman, Erin M. Kirkham, S. Kamal Naqvi, Jerilynn Radcliffe, Kristie R. Ross, Gopi B. Shah, Ignacio E. Tapia, H. Gerry Taylor, David A. Zopf, Susan Redline, Cristina M. Baldassari

Statistical and Data Sciences: Faculty Publications

Objective. Caregivers frequently report poor quality of life(QOL) in children with sleep-disordered breathing (SDB).Our objective is to assess the correlation between care-giver- and child-reported QOL in children with mild SDBand identify factors associated with differences between caregiver and child report.

Study Design. Analysis of baseline data from a multi-institutional randomized trialSetting. Pediatric Adenotonsillectomy Trial for Snoring, where children with mild SDB (obstructive apnea-hypopnea index\3) were randomized to observation or adenotonsillectomy.

Methods. The Pediatric Quality of Life Inventory (Peds QL)assessed baseline global QOL in participating children 5 to12 years old and their caregivers. Caregiver and child scores were compared. Multivariable regression …

The Online Ordering Behaviors Among Participants In The Oklahoma Women, Infants, And Children Program: A Cross-Sectional Analysis, Qi Zhang, Kayoung Park, Junzhou Zhang, Chuanyi Tang

Community & Environmental Health Faculty Publications

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a nutrition assistance program in the United States (U.S.). Participants in the program redeem their prescribed food benefits in WIC-authorized grocery stores. Online ordering is an innovative method being pilot-tested in some stores to facilitate WIC participants' food benefit redemption, which has become especially important in the COVID-19 pandemic. The present research aimed to examine the online ordering (OO) behaviors among 726 WIC households who adopted WIC OO in a grocery chain, XYZ (anonymous) store, in Oklahoma (OK). These households represented approximately 5% of WIC households who redeemed …

Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng

Theses and Dissertations--Statistics

Radiogenomics is a new direction in cancer research that focuses on the associations among radiomics, genomics and clinical outcome. Currently, the major challenge for Radiogenomics lies in the effective integration of genomics and imaging data for promising clinical outcome prediction. Herein, we propose a multivariate joint model that can integrate imaging and genomic data for better predicting the clinical outcome. Specifically, we jointly consider two multivariate group lasso models, one regresses imaging features on genomic features, and the other regresses patient’s clinical outcome on genomic features. An L1 penalty term is introduced for each variable, and weight in the penalty …

Statistical Theory For Specialized Linear Regression Adjustment Methods Compared To Multiple Linear Regression In The Presence And Absence Of Interaction Effects, Leon Su

Theses and Dissertations--Statistics

When building models to investigate outcomes and variables of interest, researchers often want to adjust for other variables. There is a variety of ways that these adjustments are performed. In this work, we will consider four approaches to adjustment utilized by researchers in various fields. We will compare the efficacy of these methods to what we call the ”true model method”, fitting a multiple linear regression model in which adjustment variables are model covariates. Our goal is to show that these adjustment methods have inferior performance to the true model method by comparing model parameter estimates, power, type I error, …

Deriving The Distributions And Developing Methods Of Inference For R2-Type Measures, With Applications To Big Data Analysis, Gregory S. Hawk

Theses and Dissertations--Statistics

As computing capabilities and cloud-enhanced data sharing has accelerated exponentially in the 21st century, our access to Big Data has revolutionized the way we see data around the world, from healthcare to investments to manufacturing to retail and supply-chain. In many areas of research, however, the cost of obtaining each data point makes more than just a few observations impossible. While machine learning and artificial intelligence (AI) are improving our ability to make predictions from datasets, we need better statistical methods to improve our ability to understand and translate models into meaningful and actionable insights.

A central goal in the …

Beta Mixture And Contaminated Model With Constraints And Application With Micro-Array Data, Ya Qi

Theses and Dissertations--Statistics

This dissertation research is concentrated on the Contaminated Beta(CB) model and its application in micro-array data analysis. Modified Likelihood Ratio Test (MLRT) introduced by [Chen et al., 2001] is used for testing the omnibus null hypothesis of no contamination of Beta(1,1)([Dai and Charnigo, 2008]). We design constraints for two-component CB model, which put the mode toward the left end of the distribution to reflect the abundance of small p-values of micro-array data, to increase the test power. A three-component CB model might be useful when distinguishing high differentially expressed genes and moderate differentially expressed genes. If the null hypothesis above …

Addressing Ascertainment Bias In The Study Of Cardiovascular Disease Burden In Opioid Use Disorders - Application Of Natural Language Processing Of Electronic Health Records, Jade Huang Singleton

Theses and Dissertations--Epidemiology and Biostatistics

In the United States, the prevalence of long-term exposure to opioid drugs, for both medically and nonmedically indicated purposes, has increased considerably since the mid-1990’s. Concerns have emerged about the potential health effects of opioid use. There is also growing interest in other possible connections with opioid use including cardiovascular disease. Electronic health records (EHR) contain information about patient care in the form of structured codes and unstructured notes. Natural language processing (NLP) provides a tool for processing unstructured textual data in EHR clinical notes and extracts useful information for research with structured formats. The purpose of this dissertation was …

Opioid Use Disorder Treatment With Buprenorphine: Analysis Of Treatment Utilization And Associated Outcomes In Kentucky, Feitong Lei

Theses and Dissertations--Epidemiology and Biostatistics

Opioid use disorder (OUD) is chronic opioid use that results in clinically significant suffering, impairment, or even death. The opioid epidemic in the United States has become a public health and economic crisis, affecting patients' well-being and the nation's overall health and welfare. Eastern Kentucky was among the first regions affected by the opioid crisis, and Kentucky has historically ranked among the top five states for age-adjusted drug overdose mortality rate.

There are three medications (buprenorphine, methadone, naltrexone) approved by the U.S. Food and Drug Administration to treat OUD. As a partial opioid agonist, buprenorphine is a safe medication for …

Framework For The Evaluation Of Perturbations In The Systems Biology Landscape And Inter-Sample Similarity From Transcriptomic Datasets — A Digital Twin Perspective, Mariah Marie Hoffman

Dissertations and Theses

One approach to interrogating the complexities of human systems in their well-regulated and dysregulated states is through the use of digital twins. Digital twins are virtual representations of physical systems that are descriptive of an individual's state of health, an object fundamentally related to precision medicine. A key element for building a functional digital twin type for a disease or predicting the therapeutic efficacy of a potential treatment is harmonized, machine-parsable domain knowledge. Hypothesis-driven investigations are the gold standard for representing subsystems, but their results encompass a limited knowledge of the full biosystem. Multi-omics data is one rich source of …

Think-Aloud Interviews: A Tool For Exploring Student Statistical Reasoning, A. Reinhart, C. Evans, Amanda Luby, J. Orellana, M. Meyer, J. Wieczorek, P. Elliott, P. Burckhardt, R. Nugent

Mathematics & Statistics Faculty Works

Think-aloud interviews have been a valuable but underused tool in statistics education research. Think-alouds, in which students narrate their reasoning in real time while solving problems, differ in important ways from other types of cognitive interviews and related education research methods. Beyond the uses already found in the statistics literature—mostly validating the wording of statistical concept inventory questions and studying student misconceptions—we suggest other possible use cases for think-alouds and summarize best-practice guidelines for designing think-aloud interview studies. Using examples from our own experiences studying the local student body for our introductory statistics courses, we illustrate how research goals should …

Identifying Patterns In The Structural Drivers Of Intrastate Conflict, Jonathan D. Moyer, Austin S. Matthews, Mickey Rafa, Yutang Xiong

Global and Public Affairs: Faculty Scholarship

Quantitative methods have been used to: (1) better predict civil conflict onset; and (2) understand causal mechanisms to inform policy intervention and theory. However, an exploration of individual conflict onset cases illustrates great variation in the characteristics describing the outbreak of civil war, suggesting that there is not one single set of factors that lead to intrastate war. In this article, we use descriptive statistics to explore persistent clusters in the drivers of civil war onset, finding evidence that some arrangements of structural drivers cluster robustly across multiple model specifications (such as young, poorly developed states with anocratic regimes). Additionally, …

Data, Knowledge Practices, And Naturecultural Worlds: Vehicle Emissions In The Anthropocene, Lindsay Poirier

Statistical and Data Sciences: Faculty Books

This chapter details the various techno-cultural assemblages giving rise to data collected to model and measure anthropogenic worlds, arguing that data-based technologies both represent and co-produce the Anthropocene. It begins with a review of scholarship emerging at the intersection of science and technology studies and information studies that advances understanding of data infrastructure and knowledge practices, and their role within the anthropogenic assemblages that shape history. Drawing on a case study describing how vehicle emissions are measured and regulated in the US, I examine the materialities and mutability of technologies designed to produce data about air quality, along with the …

Ga Pilot Perceptions Of Speech Systems To Transcribe And Submit Pireps, Deborah S. Carstens Ph.D., Pmp, Michael S. Harwin, J.D., M.S., Tianhua Li, Ph.D., Brandon J. Pitts, Ph.D., Mel Futrell, M.A., Barrett Caldwell, Ph.D.

International Journal of Aviation, Aeronautics, and Aerospace

Flying into hazardous weather can be a cause of aviation incidents and accidents. Accidents involving general aviation (GA) pilots who are not instrument rated who fly into instrument meteorological conditions (IMC) are often fatal. Pilot weather reports (PIREPs) can increase the accuracy and timeliness of current and forecasted weather conditions. They are an essential tool used by pilots to avoid flying into hazardous weather as well as meteorologists to develop and update aviation forecasts. Thus, a large number of accurate PIREPs with the best source of current weather coming from pilots and air traffic controllers are needed. Pilots are often …

Colonial Markets, Consumers, And Trade: A Comparative Analysis Of Historic Ceramics From The Bluefields Bay Area, Westmoreland, Jamaica, Lacy Risner

Murray State Theses and Dissertations

The ceramic assemblages from a British colonial settlement in Bluefields Bay, Jamaica, provide a unique window into the market availability, exchange routes, and consumption patterns of the eighteenth century. This study compares the historic ceramics collected from two sites in Bluefields Bay to one another and to other intra-island (Jamaica), intraregional (Lesser Antilles), and international (North America) colonial and postcolonial sites to reveal patterns of individual and global ceramic consumption and distribution in the emergent capitalist networks and markets of the colonial era. Integrating small British colonial sites into the networks of other more extensive studies focusing primarily on plantations …

Applying Machine Learning Algorithms For Face Mask Detections, Mackenzie Frato

Williams Honors College, Honors Research Projects

Goal: Apply multiple machine learning techniques to Face Mask images to detect if a student is wear a Face Mask and/or wearing it incorrectly or not at all. Methodology: Use 2-3 different machine learning techniques to develop this program. Will choose these techniques as I research over the semester. The best technique will be the final one used, but many will be explored. Validation techniques will be used to see which is the best technique. Timeline: Choose Dataset - October 1st, Choose techniques - October 31st, Research techniques/validation - November 31st, Begin writing code - December 13th, Finish code - …

Behavioral Predictive Analytics Towards Personalization For Self-Management – A Use Case On Linking Health-Related Social Needs, Bon Sy, Michael Wassil, Helene Connelly, Alisha Hassan

Publications and Research

The objective of this research is to investigate the feasibility of applying behavioral predictive analytics to optimize patient engagement in diabetes self-management, and to gain insights on the potential of infusing a chatbot with NLP technology for discovering health-related social needs. In the U.S., less than 25% of patients actively engage in self-health management even though self-health management has been reported to associate with improved health outcomes and reduced healthcare costs. The proposed behavioral predictive analytics relies on manifold clustering to identify subpopulations segmented by behavior readiness characteristics that exhibit non-linear properties. For each subpopulation, an individualized auto-regression model and …

Graph Neural Networks For Improved Interpretability And Efficiency, Patrick Pho

Electronic Theses and Dissertations, 2020-2023

Attributed graph is a powerful tool to model real-life systems which exist in many domains such as social science, biology, e-commerce, etc. The behaviors of those systems are mostly defined by or dependent on their corresponding network structures. Graph analysis has become an important line of research due to the rapid integration of such systems into every aspect of human life and the profound impact they have on human behaviors. Graph structured data contains a rich amount of information from the network connectivity and the supplementary input features of nodes. Machine learning algorithms or traditional network science tools have limitation …

Change Point Detection For Streaming Data Using Support Vector Methods, Charles Harrison

Electronic Theses and Dissertations, 2020-2023

Sequential multiple change point detection concerns the identification of multiple points in time where the systematic behavior of a statistical process changes. A special case of this problem, called online anomaly detection, occurs when the goal is to detect the first change and then signal an alert to an analyst for further investigation. This dissertation concerns the use of methods based on kernel functions and support vectors to detect changes. A variety of support vector-based methods are considered, but the primary focus concerns Least Squares Support Vector Data Description (LS-SVDD). LS-SVDD constructs a hypersphere in a kernel space to bound …

A Comparison Of Stacking Methods To Estimate Survival Using Residual Lifetime Data From Prevalent Cohort Studies, Zhaoheng Li

Mathematics, Statistics, and Computer Science Honors Projects

Prevalent cohort studies are widely used for their cost-efficiency and convenience. However, in such studies, only the residual lifetime can be observed. Traditionally, researchers rely on self-reported onset times to infer the underlying survival distribution, which may introduce additional bias that confounds downstream analysis. This study compares two stacking procedures and one mixture model approach that uses only residual lifetime data while leveraging the strengths of different estimators. Our simulation results show that the two stacked estimators outperform the nonparametric maximum likelihood estimator (NPMLE) and the mixture model, allowing robust and accurate estimations for underlying survival distributions.

Exploring Cyberterrorism, Topic Models And Social Networks Of Jihadists Dark Web Forums: A Computational Social Science Approach, Vivian Fiona Guetler

Graduate Theses, Dissertations, and Problem Reports (ETD)

This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists' Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in …

A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes, Michelle A. Frankot

Graduate Theses, Dissertations, and Problem Reports (ETD)

Preclinical behavioral neuroscience often uses choice paradigms to capture psychiatric symptoms. In particular, the subfield of operant research produces nested datasets with many discrete choices in a session. The standard analytic practice is to aggregate choice into a continuous variable and analyze using ANOVA or linear regression. However, choice data often have multiple interdependent outcomes of interest, violating an assumption of general linear models. The aim of the current study was to quantify the accuracy of linear mixed-effects regression (LMER) for analyzing data from a 4-choice operant task called the Rodent Gambling Task (RGT), which measures decision-making in the context …

Improving College Students’ Views And Beliefs Relative To Mathematics: A Systematic Literature Review Followed By A Multiple Case Mixed Methods Exploration Of The Experiences That Underpin Community College Students’ Attitudes, Self-Efficacy, And Values In Mathematics, Marquita H. Sea

Theses and Dissertations

Mathematics is particularly important due to its relevance in our daily lives. It is a general requirement throughout schooling. Unfortunately, many students openly declare negative views/beliefs regarding math in their personal and academic lives. These in turn, negatively influence students’ achievement related behaviors and outcomes. First, a systematic literature review was conducted to determine what types of studies/initiatives have aimed to enhance students’ views/beliefs relative to mathematics, including domain general and specific perceptions of math as well as their judgements of who is successful in mathematics and if they themselves can be successful. Specifically, the review centered on the components …

Estimating The Statistics Of Operational Loss Through The Analyzation Of A Time Series, Maurice L. Brown

Theses and Dissertations

In the world of finance, appropriately understanding risk is key to success or failure because it is a fundamental driver for institutional behavior. Here we focus on risk as it relates to the operations of financial institutions, namely operational risk. Quantifying operational risk begins with data in the form of a time series of realized losses, which can occur for a number of reasons, can vary over different time intervals, and can pose a challenge that is exacerbated by having to account for both frequency and severity of losses. We introduce a stochastic point process model for the frequency distribution …

Modelling Muscle Activation Using Emg Signal, Mercy U. Okonna

College of Graduate Studies: Theses & Dissertations

(EMG) is a method for measuring muscle activity by an electrical signal, and is useful in studying motor control, postural control, and in physical therapy. A current research topic is creating an algorithm that can use the EMG signal to reliably classify a muscle as active or inactive. This thesis presents a classification algorithm for leg muscles with a single activation spike while walking. Time is rescaled into steps, which are identified using data from cameras measuring joint angles while walking. The algorithm is based on moving averages and a convex combination of mean signal strength in active and inactive …

การเปรียบเทียบวิธีการคัดเลือกตัวแปรแบบรวมกลุ่ม สำหรับข้อมูลที่มีลักษณะการจำแนกแบบไบนารี, กรชนก ชมเชย

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานศึกษานี้เปรียบเทียบวิธีการคัดเลือกตัวแปรแบบเดียว (Single-Feature Selection) และแบบรวมกลุ่ม (Ensemble Feature Selection) ซึ่งแบ่งเป็น 2 รูปแบบคือ รูปแบบการรวมลำดับความสำคัญของตัวแปรแล้วตามด้วยการเลือกจำนวนตัวแปรที่มีความสำคัญตามเกณฑ์ที่ระบุ (Design CT: Combination followed by Thresholding) และรูปแบบการการเลือกจำนวนตัวแปรที่มีความสำคัญตามเกณฑ์ที่ระบุแล้วตามด้วยการรวมเซตของตัวแปรที่มีความสำคัญดังกล่าว (Design TC: Thresholding followed by Combination) ผู้ศึกษาได้ใช้การคัดเลือกตัวแปรจากประเภท Filter Wrapper และ Embedded โดยใช้ 10-fold cross validation ในการเปรียบเทียบค่าเฉลี่ยของ F1-score แทนประสิทธิภาพการทำนายและค่าเบี่ยงเบนของ F1-score แทนค่าความเสถียรของการทำนาย ผ่านข้อมูล 3 ชุดได้แก่ Parkinson's Disease dataset (จำนวนตัวแปรต้น(P)=ขนาดข้อมูล(N)), LSVT Voice Rehabilitation dataset (P>N) และ Colon Cancer dataset (P>>N) ใช้ XGBoost เป็นตัวแบบทำนาย จากการศึกษาภายใต้ขอบเขตดังกล่าวพบว่า การคัดเลือกตัวแปรแบบวิธีเดียวด้วย RFE จะให้ผลดีในชุดข้อมูลที่มีมิติมาก P>>N ในเกณฑ์ 2.5% 5% และ 10% แต่การคัดเลือกแบบรวมกลุ่มจะให้ผลการทำนายที่ต่างกันภายใต้ลักษณะมิติของชุดข้อมูลและเกณฑ์ที่เลือกใช้ สำหรับการรวมลำดับความสำคัญของตัวแปรในรูปแบบ Design CT ด้วยค่ากลางและค่าเฉลี่ยเลขคณิตที่เกณฑ์ log2(P) จะให้ผลการทำนายดีกว่าวิธีอื่นใน Design CT ในชุดข้อมูล P>>N แต่สำหรับชุดข้อมูล P=N และ P>N ผลการทำนายจากแต่ละวิธีใน Design CT เพิ่มประสิทธิภาพการทำนายเล็กน้อย และสำหรับ Design TC การรวมเซตของตัวแปรต้นที่มีความสำคัญด้วยวิธีอินเตอร์เซกและมัลติอินเตอร์เซกจะให้ผลดีกว่าวิธียูเนียน สำหรับชุดข้อมูล P>>N ในทุกเกณฑ์ …