Visualization and comparison of 9 different sorting algorithms: selection sort shell sort insertion sort merge sort quick sort heap sort bubble sort comb sort cocktail sort The algorithms are used in 4 types of
This study focuses on the comparison of algorithms for generating heatmaps to visually explain the learned patterns of Alzheimer's disease (AD) classification. T1-weighted volumetric MRI data were entered into a 3D CNN. Heatmaps were then generated for different visualization methods using the iNN...
Testing clustering algorithms based on the results of UMAP. Simple partitioning algorithms: K-Means and Gaussian Mixture Model (GMM); Hierarchical clustering: Agglomerative hierarchical clustering and BRICH; Graph-based: Spectral clustering, Louvain, and Leiden; Density-based: OPTICS, DBSCAN, and HDBSCAN...
First, separate data files containing the trajectory data of the considered algorithms must be generated. In the second step, the configuration of the algorithm comparison must be completed on STNWeb, and the data files must be uploaded. Finally, in the third step, a visualization is generated ...
A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies. BMC Bioinforma. 18, 105 (2017). Article CAS Google Scholar Zheng, S. C. et al. A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in ...
The use of interactive visualization has proven to enable valuable collaboration in group knowledge sharing and significantly increases individual learning as well as overall team performance [6]. Despite analysts and managers have a powerful set of data analysis and visualization algorithms, methods, ...
These primates are very close in the life evolution and, therefore, pose a problem for designing assertive algorithms to detect their phylogenetic tree. The paper associates logical and mathematical concepts inspired in signal processing and dynamical systems for the analysis of the DNA data of the ...
High Dimensional provides three approaches--T-SNE, PCA and UMAP--to do the dimensionality reduction, allowing developers to have an in-depth analysis of the relationship between high-dimensional data and to optimize algorithms based on the analysis....
Visual Progression Analysis of Event Sequence Data IEEE Transactions on Visualization and Computer Graphics (IEEE VAST2019) paper|video|slides Ke Xu, Meng Xia, Xing Mu, Yun Wang,Nan Cao EnsembleLens: Ensemble-based Visual Exploration of Anomaly Detection Algorithms with Multidimensional Data ...
Figure 3. Special algorithms handle border effects (e.g., comers) When objects are too numerous, the total number of objects in the focus area is shown, along with a subset of the labels. The labeling problem is not new. It has been extensively studied for cartographic purposes [4] where...