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

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

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

Homomorphic binary tree. حسب Jianhua He (341366)

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

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب 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. …"

Models and Dataset حسب 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 حسب 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. حسب 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. …"

Adaptive Inference for Change Points in High-Dimensional Data حسب Yangfan Zhang (6451946)

"…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …"