Relevant bibliographies by topics / Regression learner

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Regression learner'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Regression learner"

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Ahrens, Achim, Christian B. Hansen, and Mark E. Schaffer. "pystacked: Stacking generalization and machine learning in Stata." Stata Journal: Promoting communications on statistics and Stata 23, no. 4 (2023): 909–31. http://dx.doi.org/10.1177/1536867x231212426.

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The pystacked command implements stacked generalization (Wolpert, 1992, Neural Networks 5: 241–259) for regression and binary classification via Python’s scikit-learn. Stacking combines multiple supervised machine learners—the “base” or “level-0” learners—into one learner. The currently supported base learners include regularized regression, random forest, gradient boosted trees, support vector machines, and feed-forward neural nets (multilayer perceptron). pystacked can also be used as a “regular” machine learning program to fit one base learner and thus provides an easy-to-use application pr
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Gries, Stefan Th, and Stefanie Wulff. "The genitive alternation in Chinese and German ESL learners." International Journal of Corpus Linguistics 18, no. 3 (2013): 327–56. http://dx.doi.org/10.1075/ijcl.18.3.04gri.

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This paper exemplifies an approach to learner corpus data that adopts a multifactorial definition of ‘context’. We apply a logistic regression to 2,986 attestations of genitive alternation (the squirrel’s nest vs. the nest of the squirrel) from the Chinese and German sub-sections of the International Corpus of Learner English and the British component of the International Corpus of English that were coded for 12 factors. Importantly, the speakers’ L1 was included as a predictor to be able to compare properly the native speakers with the learners as well as the two learner groups with each othe
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Gervet, Theophile, Ken Koedinger, Jeff Schneider, and Tom Mitchell. "When is Deep Learning the Best Approach to Knowledge Tracing?" Journal of Educational Data Mining 12, no. 3 (2020): 31–54. https://doi.org/10.5281/zenodo.4143614.

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Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her future performance. The advent of increasingly large scale datasets has turned deep learning models for learner performance prediction into competitive alternatives to classical Markov process and logistic regression models. In an extensive empirical co
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Hao, Xiaowei, and Shanshan Han. "An Algorithm for Generating a Recommended Rule Set Based on Learner's Browse Interest." International Journal of Emerging Technologies in Learning (iJET) 13, no. 11 (2018): 102. http://dx.doi.org/10.3991/ijet.v13i11.9604.

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To personalize the recommended learning information according to the interests of the learner, a recommendation rule set generation algorithm based on learner browsing interests was proposed. First, the learner's browsing behavior was captured. A multivariate regression method was used to calculate the quantitative relationship between the learner's browsing behavior and the degree of interest in the web page to generate a learner's current interest view (CIV). With this current interest view, a content-based collaborative filtering personalized information recommendation service was provided
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Mwanthi, Mary Mbithe, Charles Misiko Wafula, and John Mwaura Mbugua. "Smallholder Farmer Engagement in School Feeding Program and Learner Participation in Public Primary Schools in MAKUENI, County, KENYA." Australian Journal of Business and Management Research 09, no. 01 (2024): 01–12. https://doi.org/10.52283/nswrca.ajbmr.20240901a01.

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Smallholder farmers’ engagement in the school feeding program was aimed at the regular supply of foodstuffs to schools and enhancing learner participation. Learners from marginalized households are affected by food shortages, poor healthcare, and a lack of nutritious meals. The study aimed to assess the influence of smallholder farmer engagement in school feeding program and learner participation. A sample of 275 was employed from a population of 875. Information was gathered using a questionnaire, and interview guide. Quantitative and qualitative information were analyzed using descriptive, a
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Jayapermana, Rama, Aradea Aradea, and Neng Ika Kurniati. "Implementation of Stacking Ensemble Classifier for Multi-class Classification of COVID-19 Vaccines Topics on Twitter." Scientific Journal of Informatics 9, no. 1 (2022): 8–15. http://dx.doi.org/10.15294/sji.v9i1.31648.

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Purpose: However, from the variety of uses of these algorithms, in general, accuracy problems are still a concern today, even accuracy problems related to multi-class classification still require further research.Methods: This study proposes a stacking ensemble classifier method to produce better accuracy by combining Logistic Regression, Random Forest, and Support Vector Machine (SVM) algorithms as first-level learners and using Logistic Regression as a meta-learner for the multi-class classification of COVID-19 vaccine topics on Twitter.Result: Based on the evaluation, the proposed Stacking
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Dewi, Desi Surlitasari, and Eka Wilany. "THE RELATIONSHIP BETWEEN LEARNER AUTONOMY AND MOTIVATION IN EFL SPEAKING CLASS." ELP (Journal of English Language Pedagogy) 8, no. 2 (2023): 194–208. http://dx.doi.org/10.36665/elp.v8i2.758.

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Despite continuous effort to establish an engaging learning environment, there is a lack of motivation among EFL learners in speaking class. Understanding the relationship between autonomy and motivation might provide insights into effective methods of instruction in EFL speaking classes when learners need to strengthen their speaking skills. This study aimed to investigate the relationship between learner autonomy and motivation in higher education, particularly in EFL speaking classes. The research method employed in this correlational study was a questionnaire to assess learner autonomy and
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Smith, Bevan I., Charles Chimedza, and Jacoba H. Bührmann. "Treatment Effect Performance of the X-Learner in the Presence of Confounding and Non-Linearity." Mathematical and Computational Applications 28, no. 2 (2023): 32. http://dx.doi.org/10.3390/mca28020032.

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This study critically evaluates a recent machine learning method called the X-Learner, that aims to estimate treatment effects by predicting counterfactual quantities. It uses information from the treated group to predict counterfactuals for the control group and vice versa. The problem is that studies have either only been applied to real world data without knowing the ground truth treatment effects, or have not been compared with the traditional regression methods for estimating treatment effects. This study therefore critically evaluates this method by simulating various scenarios that incl
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CHEN, MENG YING, and ALI MOHAMMED LUBNA. "THE EFFECT OF INTERACTION ON LEARNER SATISFACTION WITH OPEN DISTANCE LEARNING." Quantum Journal of Social Sciences and Humanities 5, no. 5 (2024): 140–48. https://doi.org/10.55197/qjssh.v5i5.443.

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Understanding the rules and characteristics of online teaching is of great importance in ensuring the teaching effectiveness of open and distance education. Assessing students’ online learning satisfaction is crucial, as it not only reflects the “learner-centered” approach but also serves as a vital measure of the quality of online teaching in open universities, particularly in the context of the Internet. One significant characteristic of open distance learning is the “separation of teaching and learning”, which can lead to feelings of loneliness among learners, ultimately affecting their onl
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Dewaele, Jean-Marc. "The Effect of Classroom Emotions, Attitudes Toward English, and Teacher Behavior on Willingness to Communicate Among English Foreign Language Learners." Journal of Language and Social Psychology 38, no. 4 (2019): 523–35. http://dx.doi.org/10.1177/0261927x19864996.

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Willingness to communicate (WTC) in a foreign language is linked to a range of interacting learner-internal and learner-external variables. The present study identified the predictors of WTC of 210 foreign language learners of English from Spain. Multiple regression analyses revealed that the strongest (negative) predictor of WTC was foreign language classroom anxiety, while foreign language enjoyment and frequency of foreign language use by the teacher were positive predictors.
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Dissertations / Theses on the topic "Regression learner"

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Khumalo, Vuyisile L. "The effects of school conditions on learner reading achievement." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/46164.

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This study aims to determine the effect of school conditions on learner reading achievement in primary schools in South Africa. Reading skills are not only imperative for further study but are essential for economic and meaningful citizenship. Initiatives such as the Quality Learning and Teaching Campaign, geared to improve the quality of education for all children and to ensure improved learner achievement have resulted in an increase in educational spending. Despite such initiatives, learner achievement remains poor. In order to measure the relative relationship between school conditions an
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Roux, Karen. "Identifying the relationship between the home environment, parental attributes and learner achievement in reading literacy." Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/66516.

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Emphasis has been placed nationally and internationally by parents, schools and communities on reading literacy skills as it is essential to be able to participate in today’s society. Reading and literacy skills underpin literacy in formal schooling. However in order for children to cope in formal schooling, children should fist acquire the necessary informal and formal literacy skills. These literacy skills can be developed through early literacy experiences gained within the home context. The home environment plays a vital role in the development and acquisition of children’s reading and lit
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Oldenkamp, Emiel. "Using supervised learning methods to predict the stop duration of heavy vehicles." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-50977.

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In this thesis project, we attempt to predict the stop duration of heavy vehicles using data based on GPS positions collected in a previous project. All of the training and prediction is done in AWS SageMaker, and we explore possibilities with Linear Learner, K-Nearest Neighbors and XGBoost, all of which are explained in this paper. Although we were not able to construct a production-grade model within the time frame of the thesis, we were able to show that the potential for such a model does exist given more time, and propose some suggestions for the paths one can take to improve on the endpo
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Sarker, Amie. "Developing Culturally Responsive Literacy Teachers: Analysis of Academic, Demographic, and Experiential Factors Related to Teacher Self-efficacy." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc177251/.

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This mixed-methods study examined teachers' culturally responsive teaching (CRT) self-efficacy beliefs and the relationships among selected academic, demographic, and experiential factors. Guided by theoretical and empirical research on CRT, teacher dispositions, and assessment in teacher education (TE) programs for culturally and linguistically diverse (CLD) students, this study utilized an extended version of Siwatu's 2007 Culturally Responsive Teaching Self-Efficacy (CRTSE) Scale to conduct correlational and comparative statistical analyses. Data sources included surveys from 265 participan
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Odendaal, Danica. "The relationship between bullying and Grade 4 boy learners' reading literacy achievement." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/62897.

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Reading can improve the quality of life for individuals and is widely considered the cornerstone of learning. However, many boys who enjoy reading are bullied. The direct, negative effects of bullying on academic achievement have been exposed in previous research. The purpose of this empirical study was to examine whether any statistical relationship existed between the low overall reading literacy achievement scores of Grade 4 boy learners and whether they experienced being the victims of peer bullying. Three research questions underpinned this quantitative, non-experimental, secondary data a
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Phahlamohlaka, Naledi Legwadi Catherine. "The relationship between Grade 5 learners’ reading literacy achievement and parental reading attitudes and behaviours." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/65462.

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This study aims to establish the relationship between reading literacy in the primary school and parental attitudes and behaviour to reading. Reading literacy is another dimension of literacy (Dubin & Kuhlman, 1992), notably the ability to understand and make use of written language (Mullis, Martin, Kennedy, Trong & Sainsbury, 2009). Despite various educational improvement initiatives undertaken by the South African Education system (ANAs, SACMEQ, TIMMS, PIRLS) as a means of creating systems to improve standards of education (Education Policy Act 2015 of 1998), learner achievement in the prima
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John, Adam. "Gender differences in syntactic complexity amongst Swedish L2 learners of English." Thesis, Högskolan i Gävle, Avdelningen för humaniora, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-29398.

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Internationally, female L2 learners of English are believed to outperform males in all areas including writing. However, in the context of Sweden, the gender gap has been reducing in recent decades. A body of literature focusing on gender differences and syntactic complexity of Swedish high school L2 learners of English using the Uppsala Learner English Corpus (ULEC) has not provided strong evidence to suggest female students outperform male students. Furthermore, the analyses of most of these studies do not take into consideration other important control variables, lack thorough statistical t
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Jones, Eli A. "A Multiple-Cutoff Regression-Discontinuity Analysis of the Effects of Tier 2 Reading Interventions in a Title I Elementary School." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6097.

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Reading failure in elementary school is highly correlated with future academic and social problems. Schools commonly use Tier 2 reading interventions in Response to Intervention (RtI) frameworks to help close the gap between at-risk readers and their peers who read on grade-level. This dissertation presents the findings of a quasi-experimental research study of the effects of three Tier 2 reading interventions in an urban Title I elementary school's RtI framework. A regression discontinuity design (RDD) with two cutoff points was used to assign 320 students in grades 1-6 to two types of Tier
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AMATO, Domenico. "A Tour of Learned Static Sorted Sets Dictionaries: From Specific to Generic with an Experimental Performance Analysis." Doctoral thesis, Università degli Studi di Palermo, 2022. http://hdl.handle.net/10447/554025.

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In recent years, in the era of Big Data, studying new methods to improve the performance of well-known procedures, such as searching in a Sorted Set, has become crucial in many fields. A new trend emerging in this scenario combines Machine Learning models with Data Structures, generating the so-called Learned Data Structures. In this thesis, we provide an in-depth experimental study of the use of these models, starting from some evidence known to experts in the field but not experimentally investigated concerning the use of very complex models such as Neural Networks. Then, we document a time/
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Nguyen, John, and Kasper Lindén. "Creating a Back Stock to Increase Order Delivery and Pickup Availability." Thesis, KTH, Hälsoinformatik och logistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252798.

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Apotek Hjärtat wants to keep developing their e-commerce website and improve retrieval and delivery of orders to customers. Click and Collect and Click and Express are two options for retrieving e-commerce orders that are available if all products in the order are present in the store. By implementing a back stock in the stores with popular e-commercial items, all products of an order will more often be present in the store. The back stock will in such a way increase the availability of Click and Collect and Click and Express. The goals for the study are to conduct a pilot study, compare metho
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Books on the topic "Regression learner"

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Vidales, A. Data Science with Matlab. Predictive Techniques: Multivariate Linear Regression and Regression Learner. Independently Published, 2019.

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Gelman, Andrew, and Deborah Nolan. Multiple regression and nonlinear models. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0010.

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This chapter covers multiple regression and links statistical inference to general topics such as lurking variables that arose earlier. Many examples can be used to illustrate multiple regression, but we have found it useful to come to class prepared with a specific example, with computer output (since our students learn to run the regressions on the computer). We have found it is a good strategy to simply use a regression analysis from some published source (e.g., a social science journal) and go through the model and its interpretation with the class, asking students how the regression resul
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Contemporary Precalculus through Applications. North Carolina School of Science and Mathematics, 2021. http://dx.doi.org/10.5149/9781469665924_departmentofmathematics.

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The first edition of Contemporary Precalculus through Applications was published in 1993, well before the widespread use of computers in the classroom. Collaborating with students and teachers across the state, faculty from the North Carolina School of Science and Mathematics (NCSSM) have steadily developed, reviewed, and tested the textbook in the years since. It is the sole textbook used in NCSSM precalculus courses. This third edition contains extensively updated data, graphics, and material attuned to contemporary technology while keeping what made the book so revolutionary when it was fir
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Gelman, Andrew, and Deborah Nolan. Teaching Statistics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.001.0001.

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Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such
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Cosgrove, Alwyn, and Craig Rasmussen. Secrets of Successful Program Design. Human Kinetics, 2021. http://dx.doi.org/10.5040/9781718225503.

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“Alwyn and Craig are two of the best teachers in the fitness industry. I only wish I'd had this resource years ago when first starting out in my career!” —Eric Cressey, President of Cressey Sports Performance “Alwyn and Craig have written something that is much more than another fitness book. This book is the state of the art in training. Whether you are a personal trainer, a sport coach, or just a fitness enthusiast, you will be happy you picked this book up.” —Michael Boyle, Owner of Mike Boyle Strength and Conditioning “If you want the best knife, go to Japan; if you want the best watch, go
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Osterlind, Steven J. The Error of Truth. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198831600.001.0001.

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The Error of Truth recounts the astonishing and unexpected tale of how quantitative thinking was invented and rose to primacy in our lives in the nineteenth and early twentieth centuries, bringing us to an entirely new perspective on what we know about the world and how we know it—even on what we each think about ourselves. Quantitative thinking is our inclination to view natural and everyday phenomena through a lens of measurable events, with forecasts, odds, predictions, and likelihood playing a dominant part. This worldview, or Weltanschauung, is unlike anything humankind had before, and it
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Witkov, Carey, and Keith Zengel. Chi-Squared Data Analysis and Model Testing for Beginners. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198847144.001.0001.

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This book is the first to make chi-squared model testing, one of the data analysis methods used to discover the Higgs boson and gravitational waves, accessible to undergraduate students in introductory physics laboratory courses. By including uncertainties in the curve fitting, chi-squared data analysis improves on the centuries old ordinary least squares and linear regression methods and combines best fit parameter estimation and model testing in one method. A toolkit of essential statistical and experimental concepts is developed from the ground up with novel features to interest even those
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Li, Quan. Using R for Data Analysis in Social Sciences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656218.001.0001.

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This book seeks to teach undergraduate and graduate students in social sciences how to use R to manage, visualize, and analyze data in order to answer substantive questions and replicate published findings. This book distinguishes itself from other introductory R or statistics books in three ways. First, targeting an audience rarely exposed to statistical programming, it adopts a minimalist approach and covers only the most important functions and skills in R that one will need for conducting reproducible research projects. Second, it emphasizes meeting the practical needs of students using R
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Book chapters on the topic "Regression learner"

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Schweinberger, Martin, and Yuki Komiya. "Chapter 3. A corpus-based comparative acoustic analysis of target-like vowel production by L1-Japanese learners and native speakers of English." In Studies in Corpus Linguistics. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/scl.119.03sch.

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This study combines acoustic phonetics, (applied) corpus linguistics, machine learning, and speech recognition to analyse the production of the monophthongal vowels / ɐ ɒ æ e ɛ i: ɪ u; ʊ ʌ / in the speech of L1-Japanese learners and L1-speakers of English based on transcripts and audio data from the Japanese spoken monologue section of the International Corpus Network of Asian Learners of English (ICNALE). The aim of this analysis is to evaluate what vowels L1-Japanese learners struggle with in terms of target-like vowel production and to provide insights into the determining factors causing d
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Ko, James. "Effective and Inspiring Teaching in STEM Classrooms: Evidence from Classroom Observations with Instrument Comparisons." In Effective Teaching Around the World. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-31678-4_26.

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AbstractThis book chapter reports findings in a case study on the video clips of 97 STEM lessons at a local secondary school. The impact of Effective and inspiring teaching on student engagement in classrooms was explored using the same high-inference classroom observation instruments. Cluster analysis indicated that effective teaching dimensions tended to cluster together. However, inspiring teaching dimensions (i.e., Flexibility, Innovative teaching, and Teaching reflective thinking) tended to cluster with Teaching collaborative learning. While there was no subject difference for inspiring t
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Sidana, Ajay, and Neeru Sidana. "The Empirical Investigation of Artificial Intelligence for Enhancing the Learner–Instructor Interaction towards Online Learning Using Multiple Regression Analysis." In The Role of Sustainability and Artificial Intelligence in Education Improvement. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003425779-10.

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Fouda, Engy. "Regression." In Learn Data Science Using Python. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0935-4_7.

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Fouda, Engy. "Regression." In Learn Data Science Using SAS Studio. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6237-5_7.

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Zhou, Hong. "Linear Regression." In Learn Data Mining Through Excel. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5982-5_2.

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Zhou, Hong. "Logistic Regression." In Learn Data Mining Through Excel. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5982-5_6.

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Zhou, Hong. "Linear Regression." In Learn Data Mining Through Excel. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9771-1_2.

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Zhou, Hong. "Logistic Regression." In Learn Data Mining Through Excel. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9771-1_6.

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Paper, David. "Scikit-Learn Regression Tuning." In Hands-on Scikit-Learn for Machine Learning Applications. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5373-1_7.

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Conference papers on the topic "Regression learner"

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Rezazadeh, Farzad, Emad Olfatbakhsh, and Andreas Kroll. "Sign Diversity: A Method for Measuring Diversity in Base Learner Selection for Ensemble Regression." In 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems (CIES). IEEE, 2025. https://doi.org/10.1109/cies64955.2025.11007635.

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Sharma, Chayanika, Venugopal Raskatla, and Vijay Kumar. "Speckle-learned Regression of Orbital Angular Momentum Superpositions." In Advanced Solid State Lasers. Optica Publishing Group, 2024. https://doi.org/10.1364/assl.2024.jd1.4.

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The coefficients of the orbital angular momentum modes in a superposition state are determined using the machine learning regression technique. Instead of directly utilizing modal intensity images, their corresponding speckle patterns are employed.
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Lu, Yuchen, Yuanqi He, Guan Wang, Chunlong Fang, and Ziyao Sun. "Multi-Target NeuralLss Regression with Learned Confidence Space." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651062.

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Wankhade, Sushama D., and Babasaheb R. Patil. "Machine Learning Based Electrical Load Prediction Using Regression Learners: A Performance Evaluation." In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). IEEE, 2024. http://dx.doi.org/10.1109/icoici62503.2024.10696398.

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G, Shreeja, Shruthi Kannan, and Soubraylu Sivakumar. "Solar Power Output Prediction with AI: Leveraging Meta Learner Ensemble Stacked Regressor." In 2024 International Conference on Integration of Emerging Technologies for the Digital World (ICIETDW). IEEE, 2024. https://doi.org/10.1109/icietdw61607.2024.10939884.

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López Flores, Walter Jeremías. "Evaluation of Neural Network and Logit Models for Classification of Default in Banking Loans." In I Conferencia Internacional de Ciencia, Tecnología e Innovación. Trans Tech Publications Ltd, 2024. http://dx.doi.org/10.4028/p-dxrv7c.

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The purpose of the study was to evaluate the performance of neural networks as modern techniques to classify the risk of default against the traditional Logit statistical method, taking a Honduran bank as a case study. The data was obtained from its credit portfolio made up of 38,156 personal loans and 9 available characteristics, choosing the most representative independent variables to design a Multilayer Perceptron type base model and its Logit equivalent to which characteristics were added to analyze their impact on the classification of the dependent variable Default, leaving in the end a
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Zhu, Xiaojin, Ji Liu, and Manuel Lopes. "No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/502.

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We present a theoretical study of algorithmic teaching in the setting where the teacher must use the same training set to teach multiple learners. This problem is a theoretical abstraction of the real-world classroom setting in which the teacher delivers the same lecture to academically diverse students. We define a minimax teaching criterion to guarantee the performance of the worst learner in the class. We prove that the teaching dimension increases with class diversity in general. For the classes of conjugate Bayesian learners and linear regression learners, respectively, we exhibit corresp
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Liao, Zhenwei, and Yongheng Wang. "Rival Learner Algorithm with Drift Adaptation for Online Data Stream Regression." In ACAI 2018: 2018 International Conference on Algorithms, Computing and Artificial Intelligence. ACM, 2018. http://dx.doi.org/10.1145/3302425.3302475.

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Kwok, David. "Predictors of students’ perceived learning in off-campus learning environment: Online interactions are not enough." In ASCILITE 2020: ASCILITE’s First Virtual Conference. University of New England, Armidale, 2020. http://dx.doi.org/10.14742/ascilite2020.0114.

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This study aimed to investigate how three online interaction variables (i.e., learner-instructor interaction, learner-content interaction, and learner-learner interaction) and self-efficacy for learning can predict students’ perceived learning in an off-campus learning environment. A total of 654 polytechnic students participated in the study. By controlling gender and age, regression results showed that self-efficacy for learning was the significantly strongest predictor of perceived learning, followed by learner-content interaction. Perceived learning and learner-instructor interaction for m
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Tchakala, Mouctar, Tahar Tafticht, and Md Jahidur Rahman. "An Efficient Approach for Short-Term Load Forecasting Using the Regression Learner Application." In 2023 4th International Conference on Clean and Green Energy Engineering (CGEE). IEEE, 2023. http://dx.doi.org/10.1109/cgee59468.2023.10351847.

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Reports on the topic "Regression learner"

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Dubeck, Margaret M., Jonathan M. B. Stern, and Rehemah Nabacwa. Learning to Read in a Local Language in Uganda: Creating Learner Profiles to Track Progress and Guide Instruction Using Early Grade Reading Assessment Results. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.op.0068.2106.

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The Early Grade Reading Assessment (EGRA) is used to evaluate studies and monitor projects that address reading skills in low- and middle-income countries. Results are often described solely in terms of a passage-reading subtask, thereby overlooking progress in related skills. Using archival data of cohort samples from Uganda at two time points in three languages (Ganda, Lango, and Runyankore-Rukiga), we explored a methodology that uses passage-reading results to create five learner profiles: Nonreader, Beginner, Instructional, Fluent, and Next-Level Ready. We compared learner profiles with re
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Finch, Holmes. Robust Methods for Regression Modeling. Instats Inc., 2025. https://doi.org/10.61700/id1rmtgty93xq1812.

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This two-day seminar provides a comprehensive exploration of robust regression methods, focusing on their application when traditional regression assumptions are violated. Participants will learn to implement nonparametric and robust techniques using R, enhancing the reliability and validity of their research findings.
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Marchese, Malvina. Advanced Non-Linear Regression Modelling. Instats Inc., 2023. http://dx.doi.org/10.61700/mrtlpflhp64q7469.

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This two-day seminar offers an in-depth introduction to non-linear regression models for cross sectional data, covering binary, multinomial, ordinal, censored, count, and the very popular quantile regression models. You will learn everything you need to know in order to understand and apply these methods in your own research. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point
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Marchese, Malvina. Advanced Non-Linear Regression Modelling. Instats Inc., 2023. http://dx.doi.org/10.61700/ovehw89kw8hwq469.

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This two-day seminar offers an in-depth introduction to non-linear regression models for cross sectional data, covering binary, multinomial, ordinal, censored, count, and the very popular quantile regression models. You will learn everything you need to know in order to understand and apply these methods in your own research. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point
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Landis, Ronald. Regression Analysis for Social and Health Science. Instats Inc., 2023. http://dx.doi.org/10.61700/me4ohse6jsdoy469.

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This comprehensive 2-day workshop will equip PhD students, professors, and professional researchers with the knowledge and skills needed to effectively use multiple regression analysis in their research. Participants will gain a deep understanding of multiple regression, learn how to use R, Excel, and Jamovi for analysis, interpret and report results, handle missing data, and enhance their research capabilities. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Jakobsen, Tor Georg. Using ChatGPT with Stata: Regression Analysis (Part I). Instats Inc., 2025. https://doi.org/10.61700/w17ywtk8775q41567.

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This workshop provides a comprehensive introduction to regression techniques essential for social science research. Participants will learn both theoretical and practical aspects of regression analysis, including OLS regression and dummy variables, using the statistical software Stata. It features hands-on exercises, detailed instructions, and AI-powered assistance from ChatGPT to clarify concepts and troubleshoot commands. Ideal for beginners, this course lays a solid foundation for mastering advanced statistical methods.
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Choquette, Gary. PR-000-16209-WEB Data Management Best Practices Learned from CEPM. Pipeline Research Council International, Inc. (PRCI), 2019. http://dx.doi.org/10.55274/r0011568.

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DATE: Wednesday, May 1, 2019 TIME: 2:00 - 3:30 p.m. ET PRESENTER: Gary Choquette, PRCI CLICK DOWNLOAD/BUY TO ACCESS THE REGISTRATION LINK FOR THIS WEBINAR Systems that manage large sets of data are becoming more common in the energy transportation industry. Having access to the data offers the opportunity to learn from previous experiences to help efficiently manage the future. But how does one manage to digest copious quantities of data to find nuggets within the ore? This webinar will outline some of the data management best practices learned from the research projects associated with CEPM.
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Espinoza, Sandra Karina, Allan Edgardo Pineda Burgos, and Marco Antonio Agüero Rodríguez. The Impact of ICT on Vegetable Farmers in Honduras. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0011193.

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Honduran farmers are at a disadvantage when dealing with intermediaries because they lack timely information about market prices. This paper first analyzes which information and communications technology (ICT) would be most suitable for sending price information to producers scattered throughout the country at a reasonable cost and in a sustainable way. Negotiations by two groups of farmers were compared: one to which market prices were not sent (control) and one to which prices were sent (treatment). A simple uninterrupted time series research design was used, followed by linear regression an
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Kaffenberger, Michelle, Danielle Sobol, and Deborah Spindelman. The Role of Low Learning in Driving Dropout: A Longitudinal Mixed Methods Study in Four Countries. Research on Improving Systems of Education (RISE), 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/070.

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Using unique longitudinal quantitative and qualitative data, we examine the role that low learning plays in driving dropout in Ethiopia, India, Peru, and Vietnam. Regression analysis using IRT-linked test scores and data on schooling attainment and dropout shows a strong, significant association with one standard deviation higher test scores associated with 50 percent lower odds of dropping out between the ages of 8 and 12, and a similar association between the ages of 12 and 15. Qualitative analysis indicates a direct relationship between low learning and dropout, with children and parents ch
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Bednall, Timothy. A Gentle Introduction to Python. Instats Inc., 2023. http://dx.doi.org/10.61700/ywg7hgz3gf12y469.

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This seminar teaches the basics of Python without any assumed prior knowledge of statistics or programming. Over the course of two days you'll learn how to load, save, and explore data, present your work, manipulate data, and create figures/plots. We will also showcase basic examples of using Python for prediction with regression analysis, classification, dimensionality reduction, and clustering. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.
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