# Dendritic Clustering Crate

 This crate allows for clustering of data for unsupervised tasks.
 The bayes crate currently supports K means clustering.
 Code for the Hierarchical clustering module is there but does not work at the moment

 ## Features
 - **K Means**: Standard K means clustering

 ## Disclaimer
 The dendritic project is a toy machine learning library built for learning and research purposes.
 It is not advised by the maintainer to use this library as a production ready machine learning library.
 This is a project that is still very much a work in progress.


 ## Example Usage
 This is an example of using the K means clustering module
 ```rust
 use dendritic_ndarray::ndarray::NDArray;
 use dendritic_ndarray::ops::*;
 use dendritic_clustering::k_means::*;
 use dendritic_knn::distance::*;
 use dendritic_datasets::iris::*; 

 fn main() {

     // Load datasets from saved ndarray
     let data_path = "../dendritic-datasets/data/iris.parquet";
     let (x_train, y_train) = load_iris(data_path).unwrap();

     // Iterations and K value for K means cluster
     let iterations = 5;
     let k_value = 3; 

     // Create instance of K means model
     let mut clf = KMeans::new(
         &x_train, 
         k_value, 
         iterations, 
         euclidean
     ).unwrap();

     // Get centroids
     let final_centroids = clf.fit();
     let centroids_unique = final_centroids.unique();
 }
 ```