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

“…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML by Ayush Garg (21090944)

“…The important findings of our studies are as follows: (i) there is no effect of threshold optimization on ranking metrics such as AUC and AUPR, but AUC and AUPR get affected by class-weighting and SMOTTomek; (ii) for ML methods RF and SVM, significant percentage improvement up to 375, 33.33, and 450 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy, which are suitable for performance evaluation of imbalanced data sets; (iii) for AutoML libraries AutoGluon-Tabular and H2O AutoML, significant percentage improvement up to 383.33, 37.25, and 533.33 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy; (iv) the general pattern of percentage improvement in balanced accuracy is that the percentage improvement increases when the class ratio is systematically decreased from 0.5 to 0.1; in the case of F1 score and MCC, maximum improvement is achieved at the class ratio of 0.3; (v) for both ML and AutoML with balancing, it is observed that any individual class-balancing technique does not outperform all other methods on a significantly higher number of data sets based on F1 score; (vi) the three external balancing techniques combined outperformed the internal balancing methods of the ML and AutoML; (vii) AutoML tools perform as good as the ML models and in some cases perform even better for handling imbalanced classification when applied with imbalance handling techniques. …”

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

Diversity and specificity of lipid patterns in basal soil food web resources by Jakob Kühn (7288466)

“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”

ROC curves for the test set of four models. by Meng Cao (105914)

“…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…”

UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

Optimal 8-mer and 9-mer SARS-CoV-2 epitope identification. by Mariah Hassert (5746874)

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx by Liyin Zhang (6371999)

“…Two major categories of prediction models are identified by an overview of the chosen studies: simple or logistic regression models based on clinical data and data-based ML models (continuous glucose monitoring data is most commonly used). …”

The data processing and analysis pipeline. by Xin Zhang (35492)

Face recognition accuracy of distinctive ways. by Yan Liu (25061)

RFB structure. by Yan Liu (25061)

Facial recognition flowchart in FaceNet network. by Yan Liu (25061)

Visualization results of face recognition. by Yan Liu (25061)

Test environment for research. by Yan Liu (25061)

Attention module. by Yan Liu (25061)

A simple HFS instance. by Xiang Tian (4369285)

“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”

The scheduling Gantt chart. by Xiang Tian (4369285)

“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”

Structure and computational framework of IPMMPO. by Xiang Tian (4369285)

“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”

Data types contained in and . by Xiang Tian (4369285)

“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”