* Support training from several samples
* Remove `output_bin_path` if `output_bin_path` exists
* Make several internal parameters configuable (1) minimum length of
contigs to bin (`--min-len` parameter); (2) minimum length of contigs to
break up in order to generate _must-link_ constraints (`--ml-threshold`
parameter); (3) the ratio of the number of base pairs of contigs between
1000-2500 bp smaller than this value, the minimal length will be set as
1000bp, otherwise 2500bp
* Add `-p` argument for `predict_taxonomy` mode
* Fix `np.concatenate` warning
* Remove redundant matrix when clustering
* Better pretrained models
* Faster calculating dapth using Numpy
* Use correct number of threads in `kneighbors_graph()`
* Respect number of threads (`-p` argument) when training (issue 34)