Fitness versus iterations based on different clustering algorithms. حسب Yiwei Zhao (2729758)

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Clustering results of LWQPSO-SOM algorithm. حسب Yiwei Zhao (2729758)

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Data propagation algorithm stages. حسب Fazia Akhtar (21453122)

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Algorithm for layout stage. حسب Fazia Akhtar (21453122)

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

Parameters of LWQPSO-SOM algorithm. حسب Yiwei Zhao (2729758)

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Parameters of LWQPSO-SOM algorithm. حسب Yiwei Zhao (2729758)

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The general procedure of the proposed algorithm. حسب Shayesteh Tabatabaei (12280016)

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Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Convergence curve of the DBO algorithm. حسب Ma Haohao (22177538)

"…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …"

Flowchart of network clustering. حسب Zhouzhou Liu (21560758)

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Simplifying OpenStreetMap Street Networks with Topology Preservation and Clustering حسب For Review (20439776)

"…Our multilane detection algorithm consolidates individual lane polylines into single centerlines to simplify the network. …"

Cluster categorization based on attraction type percentage. حسب Xumei Pan (21464351)

Algorithm framework. حسب Zongjin Li (38031)

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Image 2_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 6_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 2_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 4_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Image 3_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"