[SOLVED] Coms 4030a adaptive computation and machine learning assignment 2

You are required to create a Python program that implements the k-means Algorithm.
Your Python submission to moodle will be a .py file in which:
(1) The number of clusters is set to 3.
(2) The dataset below on page 3 is hard-coded into the algorithm.
Your algorithm must then:
(3) Read in from standard input a list of 6 numbers, such as
0.45
0.55
0.70
0.71
0.11
0.67The first 2 values are the initial values for cluster centre 1, so µ
1 = (0.45, 0.55).
The next 2 values are the initial values for cluster centre 2, so µ
2 = (0.70, 0.71).
The last 2 values are the initial values for cluster centre 3, so µ
3 = (0.11, 0.67).(4) Run k-means Algorithm using the hard-coded dataset and starting with cluster centres
from step 3.
(5) Halt the algorithm when the centres have converged – that is, there are no changes to the
cluster centres from one iteration to the next.(6) Compute the sum-of-squares error on the dataset with respect to the final cluster centres,
using the formula
sum-of-squares error = X
3
j=1
X
x∈cluster j
d(x, µ
j
)
2
.(7) The following value must be output using standard output:
the sum-of-squares error with respect to the final cluster centres.
Round off to 4 decimal places.
Samples:
(i) For the input values given above, the output is:
1.1053
(ii) For the following input values, the output is given below:
0.85
0.14
0.32
0.76
0.21
0.36
Output:
0.4379Use the following dataset consisting of datapoints in R
2
:
0.22, 0.33
0.45, 0.76
0.73, 0.39
0.25, 0.35
0.51, 0.69
0.69, 0.42
0.41, 0.49
0.15, 0.29
0.81, 0.32
0.50, 0.88
0.23, 0.31
0.77, 0.30
0.56, 0.75
0.11, 0.38
0.81, 0.33
0.59, 0.77
0.10, 0.89
0.55, 0.09
0.75, 0.35
0.44, 0.55