The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

The confidence curve of a binary image. by Dingming Yang (8505990)

The confidence change of the binary image after iteration. by Dingming Yang (8505990)

Homomorphic binary tree. by Jianhua He (341366)

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

“…We performed threshold optimization for converting predicted probabilities into binary predictions and identified the cut-off maximizing the sum of sensitivity and specificity.…”

Models and Dataset by M RN (9866504)

“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</p><h4><b>10 Supervised machine learning classifiers for </b><b><i>E.coli</i></b><b> genome analysis:</b></h4><ol><li><b>Logistic regression (LR): </b> A simple yet effective statistical model for binary classification, such as predicting antibiotic resistance or susceptibility in <i>E. coli</i>.…”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”