lizia-mean v0.0.1

Lizia-Mean

Module to do k-mean, the name is for mu daughter.

Install

npm install --save lizia-mean

Usage

const data = []
for (var i = 0; i < 14; i++) {
    data.push(Math.random() * 100);
}
const numClusters = 3
const dimensionOfData = 2
liziaMean(data, dimensionOfData, numClusters, (err, res) =>{
    assert(!err)
    console.log(res) //
    //[ [ 21.672581545034355,82.8807639797754,3.0398765040111186,86.22060990515324,14.972637199388107,29.470920608244388 ], ---> first data set for first cluster
    //  [ 69.6786270515767,77.68125002201222,81.88591660486652,68.21144589843846 ], ---> second data set for second cluster
    //  [ 93.62190126831484,8.198630669876295,57.3976252265612,17.733821853873664 ], ---> third data set for third cluster
    //  [ 13.228365082811194, 66.19076483105766 ], ---> first cluster
    //  [ 75.78227182822161, 72.94634796022534 ], ---> second cluster
    //  [ 75.50976324743803, 12.96622626187498 ] ---> third cluster
    // ]
});

API lizia-mean(data = [], dim = 1, numClusters = 1, cb) -> Array

data = [
       x_1, x_2, x_dim,
       ... ,
       ... ,
       x_Nx(dim-1),.., x_Nxdim
       ] // data are parsed by dim value

dimensionOfData = number to do parse the data array

numClusters = number of cluster to calculate

cb = callback called with error and response.

response = [
  data_set_1,  // data set inside of cluster 1
  data_set_2,
  ...,
  data_set_numClusters,
  cluster_1, // coords of cluster 1
  cluster_2,
  ...,
  cluster_data_set_numClusters
]

data_set_n = [
    y_1, y_2, y_dim,
       ... ,
       ... ,
    y_kx(dim-1),.., y_kxdim
]

with k the number of data in cluster n.
cluster_n = [z_1, z_2, ... , z_dim]