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())
Edit:
.values
will give the values in an array. (shape: (n,1)
.ravel
will convert that array shape to (n, )