Development of predictive models using machine learning algorithms for food adulterants bacteria detection
TM Amado, MR Bunuan, RF Chicote… - 2019 IEEE 11th …, 2019 - ieeexplore.ieee.org
One of the necessities of human to survive is food and meat is one of mainly consumed food
by humans. Thus, a level of quality of food is a must to be safely consumed. There have …
by humans. Thus, a level of quality of food is a must to be safely consumed. There have …
“TwitterSpamDetector”: a spam detection framework for Twitter
AT Kabakus, R Kara - … Journal of Knowledge and Systems Science …, 2019 - igi-global.com
Twitter is the most popular microblogging platform which lets users post status messages
called tweets. This popularity and the advanced API provided by Twitter to read and write …
called tweets. This popularity and the advanced API provided by Twitter to read and write …
Evaluating machine learning techniques for improved adaptive pedagogy
M Dlamini, WS Leung - 2018 IST-Africa Week Conference (IST …, 2018 - ieeexplore.ieee.org
Literature has shown that learning gains may be improved significantly if students are
offered individual attention. The traditional offering of such individualised attention is …
offered individual attention. The traditional offering of such individualised attention is …
[PDF][PDF] An integrated machine learning approach to studying terrorism
A Peng - Undergraduate Thesis. Yale University, 2018 - cogsci.yale.edu
This project investigates an integrated machine learning approach for classification and
analysis of global terrorist activity. In this project, we aim to make the following three …
analysis of global terrorist activity. In this project, we aim to make the following three …
Towards reproducible research: automatic classification of empirical requirements engineering papers
C Woodson, JH Hayes, S Griffioen - Proceedings of the ACMSE 2018 …, 2018 - dl.acm.org
Research must be reproducible in order to make an impact on science and to contribute to
the body of knowledge in our field. Yet studies have shown that 70% of research from …
the body of knowledge in our field. Yet studies have shown that 70% of research from …
[PDF][PDF] Enhancing stroke prediction using the waikato environment for knowledge analysis
State-of-the-art data mining tools incorporate advanced machine learning (ML) and artificial
intelligence (AI) models, and it is widely used in classification, association rules, clustering …
intelligence (AI) models, and it is widely used in classification, association rules, clustering …
Comparison of Color Identification on Soccer Robot using Color Filtering, k-NN and Naive Bayes
H Suyono, O Setyawati, S Amri - 2018 2nd International …, 2018 - ieeexplore.ieee.org
Accuracy level and computation time to identify color object are two important issues in
designing vision of soccer robot. In this research three classification methods were used to …
designing vision of soccer robot. In this research three classification methods were used to …
[图书][B] Stigma-in-Arms: An Empirical Study of Veterans' Disability Claims for the Psychological Impact of Discrimination
ER Seamone - 2020 - search.proquest.com
This study uses machine learning and regression analysis to identify characteristics of
Veterans Affairs (VA) appellate cases to understand the type of supporting evidence that is …
Veterans Affairs (VA) appellate cases to understand the type of supporting evidence that is …
Fake News and Influential Figures, an American Love Story
C Djonbalic - soar.suny.edu
Fake news has been a pervasive topic for many years, affecting both political and social
aspects of everyday life. Through the birth of various social media platforms, fake news has …
aspects of everyday life. Through the birth of various social media platforms, fake news has …
Backward sequential feature elimination and joining algorithms in machine learning
S Valsan - 2014 - scholarworks.sjsu.edu
Abstract The Naïve Bayes Model is a special case of Bayesian networks with strong
independence assumptions. It is typically used for classification problems. The Naïve Bayes …
independence assumptions. It is typically used for classification problems. The Naïve Bayes …