Behavior of the binary VKF and HGF. by Payam Piray (350782)

Comparison of binary VKF with the benchmark sampling methods. by Payam Piray (350782)

Computing the centerline from a binary segmentation. by Patrick D. McClanahan (2385076)

Binary classification task performance. by Thierry Jean (20691795)

The probabilistic learning task in Experiment 1 used for testing the VKF. by Payam Piray (350782)

Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors by Li-Pang Chen (9747423)

“…Typically, a main goal is to adopt predictors to characterize the primarily interested binary random variables. …”

Symmetry test result. by Jiyong Moon (16819302)

Fig 2 - by Dillion M. Fox (4043159)

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke by Chulho Kim (622686)

“…<div><p>Background and purpose</p><p>This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.…”

Analysis of geo-spatiotemporal data using machine learning algorithms and reliability enhancement for urbanization decision support by Kwame O. Hackman (9289505)

Ordinal regression task performance. by Thierry Jean (20691795)

Behavior of the VKF. by Payam Piray (350782)

Effects of parameters on the VKF. by Payam Piray (350782)

Behavior of the VKF in highly volatile condition for linear. by Payam Piray (350782)

UNet++ type architecture [68] used for all the problems in this paper. by Dylan D. Ray (3741823)

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…Machine learning (ML) is viewed as a promising tool for the prediction of aerobic biodegradation, one of the most important elimination pathways of organic chemicals from the environment. …”

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…Machine learning (ML) is viewed as a promising tool for the prediction of aerobic biodegradation, one of the most important elimination pathways of organic chemicals from the environment. …”

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…Machine learning (ML) is viewed as a promising tool for the prediction of aerobic biodegradation, one of the most important elimination pathways of organic chemicals from the environment. …”

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach by Sanaa Badr (20628838)

“…Testing on a new dataset revealed all models performed well, with ANN and SVM models classified all test set instances correctly, while the RF and LR models achieved 91.68% accuracy. …”

The Value of Dynamic Grip Force Modulation as a Potential Biomarkerfor Hand Function Recovery Following Stroke by Kirstin-Friederike Heise (7518953)

“…</p><p dir="ltr">We used a supervised machine learning algorithm (support vector machine, SVM, with k-fold cross-validation) for binary classification of groups (stroke versus control group), task conditions (uni- versus bimanual), and to quantify the active range of motion evaluated with upper extremity Fugl-Meyer Assessment (UEFMA) within the stroke group alone.…”