Kmeans

[dyasam]

#!/usr/bin/env python

coding: utf-8

In[62]:

Code source: Gaël Varoquaux

Modified for documentation by Jaques Grobler

License: BSD 3 clause

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import datasets
from sklearn.decomposition import PCA

import some data to play with

iris = datasets.load_iris()
X = iris.data[:, :2] # we only take the first two features.
y = iris.target

from mpl_toolkits import mplot3d
get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.axes(projection='3d')

xdata=iris.data[:,0]
ydata=iris.data[:,2]
zdata=iris.data[:,3]
label=iris.target

ax.scatter3D(xdata[100:149], ydata[100:149], zdata[100:149],marker='o')
ax.scatter3D(xdata[50:99], ydata[50:99], zdata[50:99],marker='x')
ax.scatter3D(xdata[0:49], ydata[0:49], zdata[0:49],marker='x')

In[2]:

X.shape

In[7]:

iris.data.shape,iris.target.shape

In[14]:

for i in range(0,3):
print(iris.data[i],iris.target[i])
for i in range(50,53):
print(iris.data[i],iris.target[i])
for i in range(100,103):
print(iris.data[i],iris.target[i])

In[48]:

In[138]:

#5.1 3.5 1.4 0.2
def get_mu_s():
mu_0=[5,2,0]
mu_1=[4,4,0]
mu_2=[3,2,5]

return mu_0,mu_1,mu_2

def get_distance(mu,point):
x=mu[0]-point[0]
y=mu[1]-point[1]
z=mu[2]-point[2]

return (x**2+y**2+z**2)**0.5

def get_class_for_one_instance(flower):
mu_s=get_mu_s()
d_0=get_distance(mu_s[0],flower)
d_1=get_distance(mu_s[1],flower)
d_2=get_distance(mu_s[2],flower)
if ((d_0 < d_1) and (d_0<d_2)):
return "0"
if ((d_1 < d_0) and (d_1<d_2)):
return "1"
if ((d_2 < d_1) and (d_2<d_0)):
return "2"
def my_f_1(s_1=125):
x=iris.data[s_1][0]
y=iris.data[s_1][2]
z=iris.data[s_1][3]
my_f_1=[x,y,z]
r=get_class_for_one_instance(my_f_1)
print(r)
for i in range(150):
my_f_1(i)

In[122]:

def get_flower(i):
x=iris.data[i][0]
y=iris.data[i][2]
z=iris.data[i][3]
return [x,y,z]

In[139]:

def update_mu():
hata="yok"
mu_0_counter=0.0001
mu_0_sum=0

mu_1_counter=0.0001
mu_1_sum=0

mu_2_counter=0.0001
mu_2_sum=0

c_1=[]
c_2=[]
c_3=[]
    
for i in range(150):
    my_flower_data=get_flower(i)
    
    f_class=get_class_for_one_instance(my_flower_data)
    hata="var"

    #print(f_class)
    if(f_class=="0"):
        c_1.append(my_flower_data)    
    if(f_class=="1"):
        c_2.append(my_flower_data)
        
    if(f_class=="2"):
        c_2.append(my_flower_data)
        


return c_1,c_2,c_3

In[143]:

c_1,c_2,c_3=update_mu()

In[144]:

len(c_1),len(c_2),len(c_3)

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