MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …”

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

Subjects:

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

Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

Urgent versus nonurgent binary classification performance. by Kyung Won Kwon (18150416)

Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files by Suchismita Behera (22027316)

“…<p dir="ltr">Figures represented here illustrates the <b>metaheuristic-based band selection framework</b> for hyperspectral image classification using <b>Binary Jaya Algorithm enhanced with a mutation operator</b> to improve population diversity and avoid premature convergence. …”

Class distribution for binary classes. by Toheeb Salahudeen (21368040)

“…RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. …”

Comparing the performance of One-class classifiers with their respective binary classifier. by Efrat Cohen-Davidi (19485986)

pone.0269685.t006 - Multi-class classification algorithms for the diagnosis of anemia in an outpatient clinical setting by Rajan Vohra (10689820)

Subjects:

pone.0269685.t005 - Multi-class classification algorithms for the diagnosis of anemia in an outpatient clinical setting by Rajan Vohra (10689820)

Subjects:

Receiver operating characteristic curve for each method using the validation predictions of the binary classification problem where the positive class is malignant and the negative... by Alberto Garcia-Zamalloa (319006)

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

Model 1: All Variables for binary classification. by Toheeb Salahudeen (21368040)

“…RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. …”

Applying the proposed image enhancement algorithm. by Nicodemus Songose Awarayi (18414494)

An example binary tree for H-SuperVec(X): A hierarchical structure obtained by partitioning the class labels of each parent node into equal size subsets. by Dhananjay Kimothi (8575089)

Precision-recall curve for each method using the validation predictions of the binary classification problem where the positive class is <i>malignant</i> and the negative class is... by Alberto Garcia-Zamalloa (319006)