iris.py

#!/usr/bin/env python
# coding: utf-8

# In[25]:


from sklearn.datasets import load_iris
import pandas as pd
iris = load_iris()

iris.data.shape[1]



# In[21]:


iris.target.size



# In[27]:


df = pd.DataFrame(iris.data, columns=iris.feature_names)
df["target"] = iris.target
df


# In[31]:


df.plot(kind="scatter", x="petal length (cm)", y="target",grid=True)


# In[67]:


from sklearn.model_selection import train_test_split
targets = df["target"]
new_df = df.drop(["target"], axis=1)
X_train, X_test, y_train, y_test = train_test_split(new_df, targets, test_size=0.3, random_state=42)

X_train.iloc[50], y_train.iloc[50]

iris

from sklearn.tree import DecisionTreeClassifier
clf = DecisionTreeClassifier()
clf.fit(X_train, y_train)
prediction_results = clf.predict(X_test)


# In[70]:


import numpy as np

np.array_equal(prediction_results, y_test)