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)

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

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

“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”

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:

Binary contingency table. by Lu Xiao (314030)

Experimental results for the binary relevance classifier. by Antonio Fernando Lavareda Jacob Junior (17816730)

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

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

Binary classification predictions. by Thierry Jean (20691795)

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

“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”

Binary classification task performance. by Thierry Jean (20691795)

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

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. …”

Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple tea fields.XLSX by Yangyang Liu (807797)

Class distribution for 5-class classification. by Toheeb Salahudeen (21368040)

“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”

Class distribution for 3-class classification. by Toheeb Salahudeen (21368040)

“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”

Confusion matrix for a binary outcome (adapted from Fawcett [30]). by João Albuquerque (12936572)

DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”