Performance of machine learning algorithms. حسب Wenxue Liu (6877754)

Obtained heat map for regression-based algorithms. حسب Akshansh Mishra (21001499)

الموضوعات:

Results obtained from the supervised machine learning regression-based algorithms in the present work. حسب Akshansh Mishra (21001499)

الموضوعات:

ML algorithms in cyber security. حسب Abdullah Asım Yılmaz (20715311)

Feature importance plot obtained for regression-based algorithms. حسب Akshansh Mishra (21001499)

الموضوعات:

Results obtained from the supervised classification-based machine learning algorithms to predict deposition quality. حسب Akshansh Mishra (21001499)

الموضوعات:

Algorithmic experimental parameter design. حسب Chuanxi Xing (20141665)

"…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…"

Spatial spectrum estimation for three algorithms. حسب Chuanxi Xing (20141665)

"…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…"

Comparison of accuracy and recall between different algorithms. حسب Wangyouchen Zhang (21681025)

Suggested algorithm’s key space along with comparison. حسب Nasreen Zulfiqar (21601226)

الموضوعات:

Hyperparameters’ setting for PSO algorithm. حسب Feng Shen (151470)

الموضوعات:

Image 1_A novel cross-validated machine learning based Alertix-Cancer Risk Index for early detection of canine malignancies.jpg حسب Hanan Sharif (11492534)

Table 1_A novel cross-validated machine learning based Alertix-Cancer Risk Index for early detection of canine malignancies.docx حسب Hanan Sharif (11492534)

Convergence curves for all algorithms. حسب Genliang Li (5816264)

"…<div><p>Feature Selection (FS) is a crucial component of machine learning and data mining. Its goal is to eliminate redundant and irrelevant features from a datasets, thereby enhancing the classifier's performance. …"

Parameter Settings for competitive algorithms. حسب Genliang Li (5816264)

"…<div><p>Feature Selection (FS) is a crucial component of machine learning and data mining. Its goal is to eliminate redundant and irrelevant features from a datasets, thereby enhancing the classifier's performance. …"

Comparison of algorithms from other papers. We mark the top three results in bold. حسب Wangyouchen Zhang (21681025)

Data Sheet 1_Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China.docx حسب Hanyu Zhang (1425250)

"…</p>Methods<p>UAV-LiDAR point clouds of Populus alba, Populus simonii, Pinus sylvestris, and Pinus tabuliformis from 12 sample plots, 2,622 tree in total, were obtained in North China, training and testing sets were constructed through data pre-processing, individual tree segmentation, feature extraction, Non-uniform Grid and Farther Point Sampling (NGFPS), and then four tree species were classified efficiently by two machine learning algorithms and two deep learning algorithms.…"

Results obtained from Physics based machine learning models. حسب Akshansh Mishra (21001499)

الموضوعات:

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)

Details of multiple GWO algorithm variants. حسب Genliang Li (5816264)

"…<div><p>Feature Selection (FS) is a crucial component of machine learning and data mining. Its goal is to eliminate redundant and irrelevant features from a datasets, thereby enhancing the classifier's performance. …"