IRIS Data KNN and Logistics Regression

# coding: utf-8

# In[1]:

import numpy as np
import pandas as pd


# In[2]:

from sklearn.datasets import load_iris
Iris_ds = load_iris()


# In[3]:

type(Iris_ds)


# In[4]:

print Iris_ds.DESCR


# In[5]:

print Iris_ds.feature_names


# In[6]:

print Iris_ds.target


# In[7]:

print Iris_ds.data.shape


# In[8]:

X_features = Iris_ds.data
Y_Target = Iris_ds.target


# In[9]:

print X_features.shape
print Y_Target.shape


# In[10]:

from sklearn.neighbors import KNeighborsClassifier


# In[11]:

knn = KNeighborsClassifier(n_neighbors=1)


# In[12]:

print knn


# In[13]:

knn.fit(X_features,Y_Target)


# In[14]:

X_new = [[3,5,4,1],[5,3,4,2]]


# In[15]:

knn.predict(X_new)


# In[16]:

from sklearn.linear_model import LogisticRegression
logReg = LogisticRegression()


# In[17]:

logReg.fit(X_features,Y_Target)


# In[18]:

logReg.predict(X_new)