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

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things حسب Ashok Kumar K (21441108)

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

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

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

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

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

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

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

LSTM vs ILSTM for KDDTest-21 for binary classification. حسب Asmaa Ahmed Awad (16726315)

Statistic Test for KDDTest+ and KDDTest-21 in binary classification. حسب Asmaa Ahmed Awad (16726315)

Accuracy and number of iterations for LSTM and ILSTM using KDDTest+ in binary classifications. حسب Asmaa Ahmed Awad (16726315)

Comparison between LSTM and ILSTM using LITNET-2020 in binary classification. حسب Asmaa Ahmed Awad (16726315)

Comparison between other methods in literature using KDDTest+ for binary classification. حسب Asmaa Ahmed Awad (16726315)

Comparison between LSTM, LSTM-BOA, LSTM-CBOA and ILSTM using KDDTest+ and KDDTest-21 in binary classification with average 10 runs. حسب Asmaa Ahmed Awad (16726315)

Event-driven data flow processing. حسب Yixian Wen (12201388)

"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"

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

Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …"

Experimental observation of gastruloids and shape quantification using LOCO-EFA. حسب Martijn A. de Jong (17896732)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx حسب Çaǧlar Çaǧlayan (12253934)

"…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …"