UmapViz is a toolset for multimodal unsupervised analysis in combination with the UMAP dimensionality reduction approach.
Following the original proposal by L. McInnes, the HDBScan (Hierarchical Density-Based Spatial Clustering of Applications with Noise), is applied to low dimensional projections computed by UMAP.
- Hybrid metric (based on Tanimoto similarity coefficient and Gower distance) to compute distances between data points with multiple feature types (e.g. boolean, categorical, numerical)
- Automatic provisioning of sample features to appropriate metrics according to their type.
- Fine tuning of metrics and calibration of feature type weights