Proximity Matrix in sklearn.ensemble.RandomForestClassifier

Question

I'm trying to perform clustering in Python using Random Forests. In the R implementation of Random Forests, there is a flag you can set to get the proximity matrix. I can't seem to find anything similar in the python scikit version of Random Forest. Does anyone know if there is an equivalent calculation for the python version?

Answer 1

Based on Gilles Louppe answer I have written a function. I don't know if it is effective, but it works. Best regards.

def proximityMatrix(model, X, normalize=True):      

    terminals = model.apply(X)
    nTrees = terminals.shape[1]

    a = terminals[:,0]
    proxMat = 1*np.equal.outer(a, a)

    for i in range(1, nTrees):
        a = terminals[:,i]
        proxMat += 1*np.equal.outer(a, a)

    if normalize:
        proxMat = proxMat / nTrees

    return proxMat   

from sklearn.ensemble import  RandomForestClassifier
from sklearn.datasets import load_breast_cancer
train = load_breast_cancer()

model = RandomForestClassifier(n_estimators=500, max_features=2, min_samples_leaf=40)
model.fit(train.data, train.target)
proximityMatrix(model, train.data, normalize=True)
## array([[ 1.   ,  0.414,  0.77 , ...,  0.146,  0.79 ,  0.002],
##        [ 0.414,  1.   ,  0.362, ...,  0.334,  0.296,  0.008],
##        [ 0.77 ,  0.362,  1.   , ...,  0.218,  0.856,  0.   ],
##        ..., 
##        [ 0.146,  0.334,  0.218, ...,  1.   ,  0.21 ,  0.028],
##        [ 0.79 ,  0.296,  0.856, ...,  0.21 ,  1.   ,  0.   ],
##        [ 0.002,  0.008,  0.   , ...,  0.028,  0.   ,  1.   ]])