<p>No specific dataset needed; you can make a very simple csv:</p>
<pre><code>1, 2
3, 4
5, 6
</code></pre>
<p>Then, on the systems I've tried, I get</p>
<pre><code>$ bin/mlpack_allknn -r f.csv -v -k 3
[DEBUG] Compiled with debugging symbols.
[WARN ] Neither --neighbors_file nor --distances_file is specified, so the nearest neighbor search results will not be saved!
[INFO ] Loading 'f.csv' as CSV data. Size is 2 x 3.
[INFO ] Loaded reference data from 'f.csv' (2 x 3).
[INFO ] Building reference tree...
[INFO ] Tree built.
[INFO ] Searching for 3 nearest neighbors with dual-tree kd-tree search...
[INFO ] 3 node combinations were scored.
[INFO ] 6 base cases were calculated.
[INFO ] Search complete.
pÛyg_neighbors
pÛyg_neighborsExecution parameters:
pÛyn parameter distances_file: ""
pÛyn parameter help: false
pÛyrameter info: ""
pÛyrameter input_model_file: ""
pÛydel_fileer k: 3
pÛyfileer leaf_size: 20
pÛyfileer naive: false
pÛyfileer neighbors_file: ""
pÛyfileer output_model_file: ""
pÛyodel_filer query_file: ""
pÛyodel_filer random_basis: false
pÛyodel_filer reference_file: f.csv
pÛyodel_filer seed: 0
pÛy_filer single_mode: false
pÛy_filer tree_type: kd
pÛy_filer verbose: true
pÛy_filer version: false
pÛy_filer
pÛy_filerProgram timers:
pÛy_filer computing_neighbors: 0.000053s
pÛyg_neighbors loading_data: 0.000186s
pÛyg_neighbors total_time: 0.001866s
pÛyg_neighbors tree_building: 0.000051s
</code></pre>
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