Scikit learn decistion tree

from sklearn import tree
X = [[0, 0], [1, 1]]
Y = [0, 1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, Y)

Source: scikit-learn.org

Scikit learn decistion tree

>>> from sklearn.datasets import load_iris
>>> from sklearn.model_selection import cross_val_score
>>> from sklearn.tree import DecisionTreeClassifier
>>> clf = DecisionTreeClassifier(random_state=0)
>>> iris = load_iris()
>>> cross_val_score(clf, iris.data, iris.target, cv=10)
...                             
...
array([ 1.     ,  0.93...,  0.86...,  0.93...,  0.93...,
        0.93...,  0.93...,  1.     ,  0.93...,  1.      ])

Source: scikit-learn.org

Similar codes

0 vote128 views1 answer
Dataframe groupby rank by multiple column value
Python
0 vote130 views1 answer
Pass query params django template
Python Django
1 vote109 views1 answer
Python hide details
Python
0 vote100 views1 answer
Python make an object hashable
Python
1 vote115 views1 answer
Seaborn jointplot regression
Python
1 vote91 views1 answer
Networkx remove nodes with degree
Python
1 vote86 views3 answers
Dfs algorithm
Python
1 vote100 views2 answers
How to add up a list in python
Python
1 vote101 views2 answers
Stingray
Python
0 vote100 views2 answers
Select list of columns pandas
Python