Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

Feature selection process. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Feature selection convergence time comparison of various binary metaheuristic algorithms. by Amal H. Alharbi (21755906)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

Subjects:

The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

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

a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

Subjects:

Boxplots analysis of the tested algorithms using average error rate across 21 datasets. by Nebojsa Bacanin (13932723)

Subjects:

Schematic of iteration process of IDE-IIGA. by Ling Zhao (111365)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

Subjects:

Histograms of various water quality parameters, including pH, Hardness, Solids, Chloramines, Sulfate, Organic Carbon, Trihalomethanes, Turbidity, and a binary portability check. by Amal H. Alharbi (21755906)

Proposed Algorithm. by Hend Bayoumi (22693738)

Subjects:

Homomorphic binary tree. by Jianhua He (341366)

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

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

S1 Dataset - Novel chaotic oppositional fruit fly optimization algorithm for feature selection applied on COVID 19 patients’ health prediction by Nebojsa Bacanin (13932723)

Subjects: