On optimal segmentation and parameter tuning for multiple change-point detection and inference حسب Christina Parpoula (12870377)

"…Within this framework, a recursive optimization algorithm is developed that is capable of exploring and fine tuning these two input parameters, and optimally segmenting a time series. …"

Comparative Analysis of Mitosis Detection Method. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Demographic features of study population, including the sub cohorts of suicide cases and controls. حسب Yuval Barak-Corren (4919563)

الموضوعات:

Model ROC curve (AUC = 0.77). حسب Yuval Barak-Corren (4919563)

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Summary statistics and overall performance of the suicide prediction model. حسب Yuval Barak-Corren (4919563)

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Comparison of odds-ratio of different diagnostic codes among MS cohort vs. the general population. حسب Yuval Barak-Corren (4919563)

الموضوعات:

Comparing predictive model performance on the MS validation set using different training sets to build the model. حسب Yuval Barak-Corren (4919563)

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Manhattan plot comparing risk factors for suicidal behavior among MS patients (blue) vs. the general population (red). حسب Yuval Barak-Corren (4919563)

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Sensitivity and Specificity Analysis. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

CSI, Balanced accuracy, and FMI Analysis. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Architecture of CDL Network. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Hyper-parameter tuning of the proposed model. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Accuracy and F-Measure Analysis. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

FPR and FNR analysis. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Markedness and NLR Analysis. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Accuracy vs loss for varying epochs. حسب Afnan M. Alhassan (18349378)

"…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …"

Example EternaBrain-SAP solutions to Eterna100 puzzles. حسب Rohan V. Koodli (6889322)

Flow of complete face detection method. حسب Yingying Mei (13817440)

"…To solve these problems, based on the improvement of adaptive boosting to improve the accuracy of face detection, the study proposes a residual network 18-layer face feature extraction algorithm based on hybrid domain attention mechanism algorithm. …"

Proposed feature sets and description. حسب Arta Misini (19929042)

"…The results reveal that lexical features are the most effective set of linguistic features, significantly improving the performance of various algorithms in the authorship attribution task. Among the machine learning algorithms evaluated, XGBoost demonstrated the best overall performance, achieving an F1 score of 0.982 on literary works and 0.905 on newsroom columns. …"

Distribution of samples by author. حسب Arta Misini (19929042)

"…The results reveal that lexical features are the most effective set of linguistic features, significantly improving the performance of various algorithms in the authorship attribution task. Among the machine learning algorithms evaluated, XGBoost demonstrated the best overall performance, achieving an F1 score of 0.982 on literary works and 0.905 on newsroom columns. …"