MATLAB wrapper for umap

This repo provides a simple wrapper for umap

Installation

  1. Install umap using conda install -c conda-forge umap-learn
  2. Install h5py using conda install h5py
  3. Install condalab
  4. Run conda.init to configure condalab in MATLAB

Use

u = umap();
R = u.fit(X);

Parameters and options

Many of the parameters and options in umap are exposed in the object, and you can change these directly from MATLAB. For example:

u = umap

  umap with properties:

             n_neighbors: 15
            n_components: 2
                  metric: 'euclidean'
           learning_rate: 1
                min_dist: 0.1000
                  spread: 1
        set_op_mix_ratio: 1
      local_connectivity: 1
      repulsion_strength: 1
    negative_sample_rate: 5
    transform_queue_size: 4
      target_n_neighbors: -1
           target_weight: 0.5000
          transform_seed: 42


u.n_neighbors = 10;
u.metric = 'precomputed';

License

GPL