eval_cluster_performance {Melissa} | R Documentation

## Evaluate clustering performance

### Description

`eval_cluster_performance` is a wrapper function for computing clustering performance in terms of ARI and clustering assignment error.

### Usage

    eval_cluster_performance(obj, C_true)

### Arguments

`obj` | Output of Melissa inference object.
`C_true` | True cluster assignemnts.

### Value

The 'melissa' object, with an additional slot named 'clustering', containing the ARI and clustering assignment error performance.

### Author(s)

C.A.Kapourani C.A.Kapourani@ed.ac.uk

### See Also

`create_melissa_data_obj`, `melissa`, `filter_regions`, `eval_imputation_performance`, `eval_cluster_performance`

### Examples

    ## Extract synthetic data
    dt <- melissa_synth_dt

    # Partition to train and test set
    dt <- partition_dataset(dt)

    # Create basis object from BPRMeth package
    basis_obj <- BPRMeth::create_rbf_object(M = 3)

    # Run Melissa
    melissa_obj <- melissa(X = dt$met, K = 2, basis = basis_obj, vb_max_iter = 10,
      vb_init_nstart = 1, is_parallel = FALSE, is_verbose = FALSE)

    # Compute cluster performance
    melissa_obj <- eval_cluster_performance(melissa_obj, dt$opts$C_true)

    cat("ARI: ", melissa_obj$clustering$ari)

[Package Melissa version 1.6.0 Index]