Hi everyone,
I'm using decision tree classifier from the scikit-learn package in python
3.4, and I want to get the corresponding leaf node id for each of my input
data point.
For example, my input data array (three records, 4d each) looks like this:
array([[ 5.1, 3.5, 1.4, 0.2],
[ 4.9, 3. , 1.4, 0.2],
[ 4.7, 3.2, 1.3, 0.2]])
and let's suppose the corresponding leaf nodes for each record are 16, 5
and 45 respectively. I want my output to be:
leaf_node_id = array([16, 5, 45])
I have read through the scikit-learn mailing list and related questions on
StackOverflow but I still can't get it to work. Here is some hint I found
on the mailing list, but still does not work.
http://sourceforge.net/p/scikit-learn/mailman/message/31728624/
Below is the code I'm using and it raises the error at the final step. At
the end of the day, I want to write a function GetLeafNodes(clf, X_input)
that returns an array of corresponding leaf nodes of the input data X_input
when clf is the decision tree classifier object. Any suggestion is very
appreciated.
from sklearn.datasets import load_irisfrom sklearn import tree
# load data and divide it to train and validation
iris = load_iris()
num_train = 100
X_train = iris.data[:num_train,:]
X_valida = iris.data[num_train:,:]
y_train = iris.target[:num_train]
y_valida = iris.target[num_train:]
# fit the decision tree using the train data set
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X_train, y_train)
# Now I want to know the corresponding leaf node id for each of my
training data points
clf.tree_.apply(X_train)
# This gives the error message
below:---------------------------------------------------------------------------ValueError
Traceback (most recent call
last)<ipython-input-17-2ecc95213752> in <module>()----> 1
clf.tree_.apply(X_train)
_tree.pyx in sklearn.tree._tree.Tree.apply (sklearn/tree/_tree.c:19595)()
ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'double'
------------------------------------------------------------------------------
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