[HTML][HTML] Faradaic deionization technology: Insights from bibliometric, data mining and machine learning approaches
E Aytaç, A Fombona-Pascual, JJ Lado, EG Quismondo… - Desalination, 2023 - Elsevier
Faradaic deionization (FDI) is an emerging water treatment technology based on electrodes
able to remove ionic species from water by charge transfer reactions. It is a young and …
able to remove ionic species from water by charge transfer reactions. It is a young and …
FS/DS: A theoretical framework for the dual analysis of feature space and data space
With the surge of data-driven analysis techniques, there is a rising demand for enhancing
the exploration of large high-dimensional data by enabling interactions for the joint analysis …
the exploration of large high-dimensional data by enabling interactions for the joint analysis …
DT-SNE: t-SNE discrete visualizations as decision tree structures
Visualizations are powerful tools that are commonly used by data scientists to get more
insights about their high dimensional data. One can for example cite t-SNE, which is …
insights about their high dimensional data. One can for example cite t-SNE, which is …
A Topic Modeling Approach to Discover the Global and Local Subjects in Membrane Distillation Separation Process
Membrane distillation (MD) is proposed as an environmentally friendly technology of
emerging interest able to aid in the resolution of the worldwide water issue and brine …
emerging interest able to aid in the resolution of the worldwide water issue and brine …
Gradient-based explanation for non-linear non-parametric dimensionality reduction
Dimensionality reduction (DR) is a popular technique that shows great results to analyze
high-dimensional data. Generally, DR is used to produce visualizations in 2 or 3 …
high-dimensional data. Generally, DR is used to produce visualizations in 2 or 3 …
Mesoscopic structure graphs for interpreting uncertainty in non-linear embeddings
Probabilistic-based non-linear dimensionality reduction (PB-NL-DR) methods, such as t-
SNE and UMAP, are effective in unfolding complex high-dimensional manifolds, allowing …
SNE and UMAP, are effective in unfolding complex high-dimensional manifolds, allowing …
DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting Machine
P Salmanian, A Chatzimparmpas, AC Karaca… - arXiv preprint arXiv …, 2024 - arxiv.org
Dimensionality Reduction (DR) techniques such as t-SNE and UMAP are popular for
transforming complex datasets into simpler visual representations. However, while effective …
transforming complex datasets into simpler visual representations. However, while effective …
VERA: Generating Visual Explanations of Two-Dimensional Embeddings via Region Annotation
PG Poličar, B Zupan - arXiv preprint arXiv:2406.04808, 2024 - arxiv.org
Two-dimensional embeddings obtained from dimensionality reduction techniques, such as
MDS, t-SNE, and UMAP, are widely used across various disciplines to visualize high …
MDS, t-SNE, and UMAP, are widely used across various disciplines to visualize high …
[PDF][PDF] Natively Interpretable t-SNE
E Couplet, P Lambert, M Verleysen… - … of AIMLAI workshop, 2023 - dial.uclouvain.be
The visual exploration of high-dimensional (HD) data has gained popularity through the use
of dimensionality reduction (DR) techniques such as t-SNE and UMAP. However, the …
of dimensionality reduction (DR) techniques such as t-SNE and UMAP. However, the …
Hyper-parameters Tuning and Dimension Reduction Effects on Heart Disease Prediction Using Classification Algorithms
M Divandari, D Ghabi, MK Ebrahimi - Progress in Engineering Science, 2024 - Elsevier
Heart complication is one of the most dangerous diseases that take many victims all around
the world. This paper presented heart disease prediction based on machine learning …
the world. This paper presented heart disease prediction based on machine learning …