<ul><li>Dimension reduction algorithms have proven to be useful for analyzing large-scale high-dimensional datasets.</li><li>The initial phase of these algorithms involves converting the data into a graph, but this graph is often suboptimal.</li><li>LocalMAP is a new dimensionality reduction algorithm that dynamically adjusts the graph to address this challenge.</li><li>LocalMAP helps identify and separate real clusters in the data, offering improved accuracy in cluster identification.</li></ul>

Dimension Reduction with Locally Adjusted Graphs

Discover more