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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Data Mining And Machine Learning To Improve Northern Florida’S Foster Care System, Daniel Oldham, Nathan Foster, Mihhail Berezovski
Data Mining And Machine Learning To Improve Northern Florida’S Foster Care System, Daniel Oldham, Nathan Foster, Mihhail Berezovski
Beyond: Undergraduate Research Journal
The purpose of this research project is to use statistical analysis, data mining, and machine learning techniques to determine identifiable factors in child welfare service records that could lead to a child entering the foster care system multiple times. This would allow us the capability of accurately predicting a case’s outcome based on these factors. We were provided with eight years of data in the form of multiple spreadsheets from Partnership for Strong Families (PSF), a child welfare services organization based in Gainesville, Florida, who is contracted by the Florida Department for Children and Families (DCF). This data contained a …
Using Data Science To Detect Fake News, Eliza Shoemaker
Using Data Science To Detect Fake News, Eliza Shoemaker
Senior Honors Projects, 2010-2019
The purpose of this thesis is to assist in automating the detection of Fake News by identifying which features are more useful for different classifiers. The effectiveness of different extracted features for Fake News detection are going to be examined. When classifying text with machine learning algorithms features have to be extracted from the articles for the classifiers to be trained on. In this thesis, several different features are extracted: word counts, ngram counts, term frequency-inverse document frequency, sentiment analysis, lemmatization, and named entity recognition to train the classifiers. Two classifiers are used, a Random Forest classifier and a Naïve …
Csci 381/780 Data Analytics, Kumar Ramansenthil, Nyc Tech-In-Residence Corps
Csci 381/780 Data Analytics, Kumar Ramansenthil, Nyc Tech-In-Residence Corps
Open Educational Resources
No abstract provided.
Csc 21700 Probability And Statistics For Computer Science, Evan Agovino, Nyc Tech-In-Residence Corps
Csc 21700 Probability And Statistics For Computer Science, Evan Agovino, Nyc Tech-In-Residence Corps
Open Educational Resources
No abstract provided.
Factors That Predict Success Of A Beaumont Student, Tara Limestoll
Factors That Predict Success Of A Beaumont Student, Tara Limestoll
Masters Essays
This project is an attempt to discover predictors of high school performance through the use of data science techniques and analysis of the Beaumont school 2017-2018 student body. High school success is an important factor for college admission, so being able to forecast a student's performance or identify those in need of assistance is paramount. Analysis shows that there is a strong correlation and predictive quality in the quantitative assessment results examined in this study. While results for both success and failure were significant, predictions of student success measures were more accurate than those of the failure group.
Kaggle And Click-Through Rate Prediction, Todd W. Neller
Kaggle And Click-Through Rate Prediction, Todd W. Neller
Computer Science Faculty Publications
Neller presented a look at Kaggle.com, an online Data Science and Machine Learning learning community, as a place to seek rapid, experiential peer education for most any Data Science topic. Using the specific challenge of Click-Through Rate Prediction (CTRP), he focused on lessons learned from relevant Kaggle competitions on how to perform CTRP.
A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall
A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall
Electrical & Computer Engineering and Computer Science Faculty Publications
For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …