Experiment 4: Accuracy of modularity-based consensus clustering methods on ring-of-cliques networks of varying sizes. by Yasamin Tabatabaee (18095491)

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement by Antoine Falisse (6061601)

“…The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. …”

Measures of predictive accuracy in four machine learning algorithms. by Ryan P. Strum (12411239)

Experiment 3: Comparison of FastEnsemble(Leiden-CPM) and Leiden-CPM on synthetic networks based on clustered real-world networks. by Yasamin Tabatabaee (18095491)

DeepDate model’s architecture design. by Nour Eldeen Mahmoud Khalifa (19259450)

Subjects:

Results of the Basic CNN models and the model proposed by Neto et al. [9] for the Dengue/Chikungunya data set. by Leonides Medeiros Neto (10429179)

Subjects:

A comparison among different optimizations and classifiers. by Nour Eldeen Mahmoud Khalifa (19259450)

Subjects:

Prediction percentage distribution using different algorithms applied in our research. by Md Junayed Hossain (22615268)

Subjects:

Testing accuracy and performance metrics for different DTL models. by Nour Eldeen Mahmoud Khalifa (19259450)

Subjects:

Table_1_Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning.DOCX by Maruf A. Tamal (18947776)

“…Subsequently, data cleansing, curation, and dimensionality reduction were performed to remove outliers, handle missing values, and exclude less predictive features. To identify the optimal model, the study evaluated and compared 15 SML algorithms arising from different machine learning (ML) families, including Bayesian, nearest-neighbors, decision trees, neural networks, quadratic discriminant analysis, logistic regression, bagging, boosting, random forests, and ensembles. …”

Table_2_Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning.DOCX by Maruf A. Tamal (18947776)

“…Subsequently, data cleansing, curation, and dimensionality reduction were performed to remove outliers, handle missing values, and exclude less predictive features. To identify the optimal model, the study evaluated and compared 15 SML algorithms arising from different machine learning (ML) families, including Bayesian, nearest-neighbors, decision trees, neural networks, quadratic discriminant analysis, logistic regression, bagging, boosting, random forests, and ensembles. …”

An improved Grey Wolf Optimization based heuristic initialization algorithm for feature selection in P2P lending default prediction by Muhammad Sam'an (20649621)

Testing accuracy and performance metrics for different DTL models for every class. by Nour Eldeen Mahmoud Khalifa (19259450)

Subjects:

The flow of the SP-DRL algorithm. by Jie Fang (306330)

“…The pointer network with an encoder and decoder structure is taken as the basic network for the deep reinforcement learning algorithm. A model-free reinforcement learning algorithm is designed to train network parameters to optimize the packing sequence. …”

Architecture of the EfficientNetB3-based regression model used for cattle weight prediction. by Md Junayed Hossain (22615268)

Subjects:

An overview of PHyPO. by Shehr Bano (20421706)

Subjects:

S8 Data - by Shehr Bano (20421706)

Subjects:

S6 Data - by Shehr Bano (20421706)

Subjects:

Tuning of hyper-parameters in each iteration for AMO. by Shehr Bano (20421706)

Subjects:

S5 Data - by Shehr Bano (20421706)

Subjects: