Statistical results of various algorithms. حسب ZeSheng Lin (20501356)

"…<div><p>Data classification is an important research direction in machine learning. In order to effectively handle extensive datasets, researchers have introduced diverse classification algorithms. …"

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. حسب Abdullah Asım Yılmaz (20715311)

List of the time used by each algorithm. حسب JiaMing Gong (20427837)

"…<div><p>Online imbalanced learning is an emerging topic that combines the challenges of class imbalance and concept drift. …"

Run times of two algorithms. حسب Gourab Saha (8987405)

"…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …"

“One-shot flip-flop” (1SFF) plasticity. حسب Toviah Moldwin (10866708)

الموضوعات:

Possible plasticity rules for presynaptic input- and spike-dependent- calcium for reversed calcium thresholds. حسب Toviah Moldwin (10866708)

الموضوعات:

Simulation parameters. حسب Toviah Moldwin (10866708)

الموضوعات:

Frequency-dependent pre- and post- synaptic plasticity in rate-based models. حسب Toviah Moldwin (10866708)

الموضوعات:

Different mechanisms for homeostatic plasticity. حسب Toviah Moldwin (10866708)

الموضوعات:

Possible plasticity rules for presynaptic input- and spike-dependent- calcium. حسب Toviah Moldwin (10866708)

الموضوعات:

The calcitron model and calcium-based plasticity rules. حسب Toviah Moldwin (10866708)

الموضوعات:

Supplementary file 1_Machine learning algorithms to predict epidural-related maternal fever: a retrospective study.docx حسب Xiaohui Guo (131711)

Data Sheet 1_Exploring immune-inflammation markers in psoriasis prediction using advanced machine learning algorithms.pdf حسب Li Yang (6520)

Table 3_Machine learning-based prediction of clinical outcomes in cervical cancer using routine hematological indices: development and web implementation.xlsx حسب Gaigai Bai (13173289)

"…A panel of hematological indices was evaluated, including inflammatory markers, coagulation parameters, and metabolic indicators. Machine learning (ML) algorithms innovatively integrated with traditional regression were employed for feature selection and model development. …"

Table 5_Machine learning-based prediction of clinical outcomes in cervical cancer using routine hematological indices: development and web implementation.xlsx حسب Gaigai Bai (13173289)

"…A panel of hematological indices was evaluated, including inflammatory markers, coagulation parameters, and metabolic indicators. Machine learning (ML) algorithms innovatively integrated with traditional regression were employed for feature selection and model development. …"

Table 4_Machine learning-based prediction of clinical outcomes in cervical cancer using routine hematological indices: development and web implementation.xlsx حسب Gaigai Bai (13173289)

"…A panel of hematological indices was evaluated, including inflammatory markers, coagulation parameters, and metabolic indicators. Machine learning (ML) algorithms innovatively integrated with traditional regression were employed for feature selection and model development. …"

In a general category with finite products, morphisms of group objects that satisfy the existence of an identity element form a commutative diagram. حسب Jian-Gang Tang (21594349)

Video 2_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 حسب Tianze Liu (13922196)

Video 1_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 حسب Tianze Liu (13922196)

Data Sheet 1_Machine learning-based prediction of clinical outcomes in cervical cancer using routine hematological indices: development and web implementation.docx حسب Gaigai Bai (13173289)

"…A panel of hematological indices was evaluated, including inflammatory markers, coagulation parameters, and metabolic indicators. Machine learning (ML) algorithms innovatively integrated with traditional regression were employed for feature selection and model development. …"