I need to fit RandomForestRegressor
from sklearn.ensemble
.
forest = ensemble.RandomForestRegressor(**RF_tuned_parameters) model = forest.fit(train_fold, train_y) yhat = model.predict(test_fold)
This code always worked until I made some preprocessing of data (train_y
). The error message says:
DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
model = forest.fit(train_fold, train_y)
Previously train_y
was a Series, now it's numpy array (it is a column-vector). If I apply train_y.ravel()
, then it becomes a row vector and no error message appears, through the prediction step takes very long time (actually it never finishes...).
In the docs of RandomForestRegressor
I found that train_y
should be defined as y : array-like, shape = [n_samples] or [n_samples, n_outputs]
Any idea how to solve this issue?
Change this line:
model = forest.fit(train_fold, train_y)
to:
model = forest.fit(train_fold, train_y.values.ravel())
Explanation:
.values
will give the values in a numpy
array (shape: (n,1))
.ravel
will convert that array shape to (n, ) (i.e. flatten it)
I also encountered this situation when I was trying to train a KNN classifier. but it seems that the warning was gone after I changed:knn.fit(X_train,y_train)
toknn.fit(X_train, np.ravel(y_train,order='C'))
Ahead of this line I used import numpy as np
.
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