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

SHAP analysis for LITNET-2020 dataset. by Asmaa Ahmed Awad (16726315)

“…The results showed that the proposed ILSTM algorithm outperformed the original LSTM and other related deep-learning algorithms regarding accuracy and precision. …”

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

“…The results showed that the proposed ILSTM algorithm outperformed the original LSTM and other related deep-learning algorithms regarding accuracy and precision. …”

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

Initial parameter settings for the optimization algorithms. by Doaa Sami Khafaga (21463870)

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

“…Our results show that deep learning and optimization </p><p dir="ltr">methods, such as the binary GWO algorithm, can be successfully applied to melanoma diagnosis. …”

SHAP analysis. 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. …”

SHAP analysis mean value. 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. …”

Bar chart comparing the average fitness values of various feature selection algorithms. by Doaa Sami Khafaga (21463870)

Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. by Doaa Sami Khafaga (21463870)

SHAP bar plot. by Meng Cao (105914)

Subjects:

SHAP summary plot. by Meng Cao (105914)

Subjects:

Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms. by Doaa Sami Khafaga (21463870)

Confusion matrices for KDDTest+ in binary classification. by Asmaa Ahmed Awad (16726315)

Shap analysis for NSL-KDD in binary classification. by Asmaa Ahmed Awad (16726315)

Confusion matrices for KDDTest-21 in binary classification. by Asmaa Ahmed Awad (16726315)

Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

Confusion matrices for LITNET-2020 dataset in binary classification. by Asmaa Ahmed Awad (16726315)

LSTM vs ILSTM for LITNET-2020 in binary classification. by Asmaa Ahmed Awad (16726315)