`predict` fails for multioutput ensemble models with non-numeric DVs

Description

Multioutput forest models assume that the dependent variables are numeric. Passing string DVs returns the following error:

ValueError: could not convert string to float:

I’m going to take a stab at submitting a fix today, but I wanted to file an issue to document the problem in case I’m not able to finish a fix.

Steps/Code to Reproduce

I wrote a test based on ensemble/tests/test_forest:test_multioutput which currently fails:

def check_multioutput_string(name):
    # Check estimators on multi-output problems with string outputs.

    X_train = [[-2, -1], [-1, -1], [-1, -2], [1, 1], [1, 2], [2, 1], [-2, 1],
               [-1, 1], [-1, 2], [2, -1], [1, -1], [1, -2]]
    y_train = [["red", "blue"], ["red", "blue"], ["red", "blue"], ["green", "green"],
               ["green", "green"], ["green", "green"], ["red", "purple"],
               ["red", "purple"], ["red", "purple"], ["green", "yellow"],
               ["green", "yellow"], ["green", "yellow"]]
    X_test = [[-1, -1], [1, 1], [-1, 1], [1, -1]]
    y_test = [["red", "blue"], ["green", "green"], ["red", "purple"], ["green", "yellow"]]

    est = FOREST_ESTIMATORS[name](random_state=0, bootstrap=False)
    y_pred = est.fit(X_train, y_train).predict(X_test)
    assert_array_almost_equal(y_pred, y_test)

    if name in FOREST_CLASSIFIERS:
        with np.errstate(divide="ignore"):
            proba = est.predict_proba(X_test)
            assert_equal(len(proba), 2)
            assert_equal(proba[0].shape, (4, 2))
            assert_equal(proba[1].shape, (4, 4))

            log_proba = est.predict_log_proba(X_test)
            assert_equal(len(log_proba), 2)
            assert_equal(log_proba[0].shape, (4, 2))
            assert_equal(log_proba[1].shape, (4, 4))


@pytest.mark.filterwarnings('ignore:The default value of n_estimators')
@pytest.mark.parametrize('name', FOREST_CLASSIFIERS_REGRESSORS)
def test_multioutput_string(name):
    check_multioutput_string(name)

Expected Results

No error is thrown, can run predict for all ensemble multioutput models

Actual Results

ValueError: could not convert string to float: <DV class>

Versions

I replicated this error using the current master branch of sklearn (0.21.dev0).

[amueller]

Feel free to submit a PR if you like

[jnothman]

I suspect this case is handled just fine in KNNClassifier and DecisionTreeClassifier, so we should probably handle it here… and add common tests.