The architecture of LSTM cell. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

The architecture of ILSTM. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Parameter setting for LSTM. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

LITNET-2020 data splitting approach. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Transformation of symbolic features in NSL-KDD. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

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

الموضوعات:

Binary contingency table. حسب Lu Xiao (314030)

Top-performing model configuration and performance by algorithm type. حسب Uğur Ejder (22683228)

الموضوعات:

Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files حسب Suchismita Behera (22027316)

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

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

ROC curve for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"

Confusion matrix for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"

ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. حسب Uğur Ejder (22683228)

الموضوعات:

The accuracy score change matrix following model development. حسب Uğur Ejder (22683228)

الموضوعات:

The comparison of the accuracy score of the benchmark and the proposed models. حسب Uğur Ejder (22683228)

الموضوعات:

The prediction accuracy of simple versus hybrid models. حسب Uğur Ejder (22683228)

الموضوعات:

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

الموضوعات:

The statistical description of the original data set of the patients (<i>n</i> = 162). حسب Uğur Ejder (22683228)

الموضوعات:

Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). حسب Uğur Ejder (22683228)

الموضوعات: