Draft release of v0.1.3

Author: PyDataBlog

Project.toml

@@ -1,7 +1,7 @@
 name = "ParallelKMeans"
 uuid = "42b8e9d4-006b-409a-8472-7f34b3fb58af"
 authors = ["Bernard Brenyah", "Andrey Oskin"]
-version = "0.1.2"
+version = "0.1.3"
 
 [deps]
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"

docs/src/index.md

@@ -1,9 +1,5 @@
 # [ParallelKMeans.jl Package](https://github.com/PyDataBlog/ParallelKMeans.jl)
 
-```@contents
-Depth = 4
-```
-
 ## Motivation
 
 It's actually a funny story led to the development of this package.
@@ -61,13 +57,14 @@ git checkout experimental
 - [X] Interface for inclusion in Alan Turing Institute's [MLJModels](https://github.com/alan-turing-institute/MLJModels.jl#who-is-this-repo-for).
 - [X] Full Implementation of Triangle inequality based on [Elkan - 2003 Using the Triangle Inequality to Accelerate K-Means"](https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf).
 - [ ] Implementation of [Geometric methods to accelerate k-means algorithm](http://cs.baylor.edu/~hamerly/papers/sdm2016_rysavy_hamerly.pdf).
+- [ ] Support for other distance metrics supported by [Distances.jl](https://github.com/JuliaStats/Distances.jl#supported-distances).
 - [ ] Native support for tabular data inputs outside of MLJModels' interface.
 - [ ] Refactoring and finalizaiton of API desgin.
 - [ ] GPU support.
-- [ ] Even faster Kmeans implementation based on recent literature.
+- [ ] Implementation of other K-Means algorithm variants based on recent literature.
 - [ ] Optimization of code base.
 - [ ] Improved Documentation
-- [ ] More benchmark tests
+- [ ] More benchmark tests.
 
 ## How To Use
 
@@ -105,8 +102,8 @@ r.converged             # whether the procedure converged
 
 - [Lloyd()](https://cs.nyu.edu/~roweis/csc2515-2006/readings/lloyd57.pdf)
 - [Hamerly()](https://www.researchgate.net/publication/220906984_Making_k-means_Even_Faster)
+- [Elkan()](https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf)
 - [Geometric()](http://cs.baylor.edu/~hamerly/papers/sdm2016_rysavy_hamerly.pdf) - (Coming soon)
-- [Elkan()](https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf) - (Coming soon)
 - [MiniBatch()](https://www.eecs.tufts.edu/~dsculley/papers/fastkmeans.pdf) - (Coming soon)
 
 ### Practical Usage Examples
@@ -175,9 +172,10 @@ ________________________________________________________________________________
 
 ## Release History
 
-- 0.1.0 Initial release
-- 0.1.1 Added interface for MLJ
-- 0.1.2 Added Elkan algorithm
+- 0.1.0 Initial release.
+- 0.1.1 Added interface for MLJ.
+- 0.1.2 Added Elkan algorithm.
+- 0.1.3 Faster & optimized execution.
 
 ## Contributing
 

src/mlj_interface.jl

@@ -142,7 +142,7 @@ function MMI.transform(m::KMeans, fitresult, Xnew)
         DMatrix = convert(Array{Float64, 2}, MMI.matrix(Xnew, transpose=true))
     end
 
-    # TODO: Warn users if fitresult is from a `non-converged` fit?
+    # Warn users if fitresult is from a `non-converged` fit
     if !fitresult[end].converged
         @warn "Failed to converged. Using last assignments to make transformations."
     end