An example of 2-dimensional non-linearly separable and non-separable data for binary classification. حسب Yuji Oyamada (11714754)

Homogeneity and Structure Identification in Semiparametric Factor Models حسب Chaohui Guo (9460039)

"…In addition, a binary segmentation based algorithm is also developed to identify the homogeneous groups in loading parameters, producing more efficient estimation by pooling information across units within the same group. …"

Illustration of the four steps in constructing the point feature binary mask. حسب Luka Maisuradze (8791229)

Three main modules involved in the identification of ceRNA-miRNA triplets. حسب Yi-Wen Hsiao (13767916)

Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model حسب Rui Li (4631)

"…To this end, we propose a homogeneity identification algorithm based on binary segmentation. …"

Confusion metrics using LR-HaPi algorithm. حسب Akib Mohi Ud Din Khanday (19065631)

"…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …"

Confusion metrics using MNB-HaPi algorithm. حسب Akib Mohi Ud Din Khanday (19065631)

"…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …"

Confusion metrics using DT-HaPi algorithm. حسب Akib Mohi Ud Din Khanday (19065631)

"…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …"

Confusion metrics using SVM-HaPi algorithm. حسب Akib Mohi Ud Din Khanday (19065631)

"…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …"

Proposed framework for propaganda identification. حسب Akib Mohi Ud Din Khanday (19065631)

"…This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). …"

Graphical representation of KerTAD algorithm. حسب Luka Maisuradze (8791229)

Flow chart of the algorithm. حسب Mukesh Karunanethy (18422857)

Exemplary application of DDQR in the storage and retrieval of DNA barcode sequence for plant material. حسب Yujun Wang (1947196)

Binary leaf image rotated anti-clock wise from the origin degree to 40^<i>o</i>, 80^<i>o</i>, 120^<i>o</i>, and 160^<i>o</i> from left to ri... حسب Ali Ahmed (2567584)

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... حسب G. Christopher Marais (21492084)

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

"…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. Binary mixtures of bacteria showed all three reliably identified organisms down to 1% relative abundance, while only the relative abundance estimates of Centrifuge and CLARK were accurate. …"

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

An overview of our ceRNAR package. حسب Yi-Wen Hsiao (13767916)

Dependence of user identification time on the size of model library. حسب Mukesh Karunanethy (18422857)

"…This is applicable to the ML based algorithms which include building of binary classifier models (also known as <i>enrollment</i> in the context of biometrics). …"

Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx حسب Veera Narayana Balabathina (22518524)

"…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …"