- Added on December 14 2023
- https://chat.openai.com/g/g-3x0pPEJvw-isomaptric
How to use Isomaptric?
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Step 1 ： Click the open gpts about Isomaptric button above, or the link below.
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Step 2 ： Follow some prompt about Isomaptric words that pop up, and then operate.
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Step 3 ： You can feed some about Isomaptric data to better serve your project.
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Step 4 ： Finally retrieve similar questions and answers based on the provided content.
FAQ from Isomaptric?
Isomaptric, also known as isometric mapping, is a nonlinear dimensionality reduction (NLDR) technique used to transform high-dimensional data into lower-dimensional space. It is based on the preservation of pairwise geodesic distances between data points in the high-dimensional space. Isomaptric is a popular technique used in machine learning and data analysis.
Isomaptric first constructs a neighborhood graph based on the Euclidean distance between data points. It then computes the shortest path between each pair of points on the graph using Dijkstra's algorithm. Finally, it uses classical multidimensional scaling (MDS) to find a low-dimensional embedding that preserves the pairwise distances. Isomaptric is computationally efficient and can handle complex nonlinear relationships between data points.
Isomaptric has several advantages over other NLDR techniques. It can handle data with complex nonlinear relationships and can find a low-dimensional embedding that preserves the global structure of the data. Isomaptric is also relatively insensitive to noise in the data and can handle missing values. Additionally, Isomaptric can be easily implemented and is computationally efficient compared to some other NLDR techniques.