multiple outputs regression

[Fa20]

Hallo,

I have regression Problem with 5 targest and need to perdict them simultaneously. is it possible to use mlens?
I have tried RF, xgboost as well as NN but the results are not good . size of my data 2800 samples.

I run the example in the tutorial but got the following error

``´ <<ImportError Traceback (most recent call last)
Cell In[101], line 1
----> 1 from mlens.ensemble import SuperLearner
2 from sklearn.linear_model import LogisticRegression
3 from sklearn.ensemble import RandomForestClassifier

File ~\anaconda3\Lib\site-packages\mlens\ensemble_init_.py:12
1 """ML-Ensemble
2
3 :author: Sebastian Flennerhag
(...)
9 can be used in conjunction with any other standard estimator.
10 """
---> 12 from .super_learner import SuperLearner
13 from .blend import BlendEnsemble
14 from .subsemble import Subsemble

File ~\anaconda3\Lib\site-packages\mlens\ensemble\super_learner.py:12
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
7 Super Learner class. Fully integrable with Scikit-learn.
8 """
10 from future import division
---> 12 from .base import BaseEnsemble
13 from ..index import FoldIndex, FullIndex
16 class SuperLearner(BaseEnsemble):

File ~\anaconda3\Lib\site-packages\mlens\ensemble\base.py:20
17 import warnings
19 from .. import config
---> 20 from ..parallel import Layer, ParallelProcessing, make_group
21 from ..parallel.base import BaseStacker
22 from ..externals.sklearn.validation import check_random_state

File ~\anaconda3\Lib\site-packages\mlens\parallel_init_.py:15
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
12 as handles for multiple instances and wrappers for standard parallel job calls.
13 """
14 from .backend import ParallelProcessing, ParallelEvaluation, Job, dump_array
---> 15 from .learner import Learner, EvalLearner, Transformer, EvalTransformer
16 from .layer import Layer
17 from .handles import Group, make_group, Pipeline

File ~\anaconda3\Lib\site-packages\mlens\parallel\learner.py:24
19 from ._base_functions import (
20 slice_array, set_output_columns, assign_predictions, score_predictions,
21 replace, save, load, prune_files, check_params)
22 from .base import OutputMixin, ProbaMixin, IndexMixin, BaseEstimator
---> 24 from ..metrics import Data
25 from ..utils import safe_print, print_time, format_name, assert_valid_pipeline
26 from ..utils.exceptions import (NotFittedError, FitFailedWarning,
27 ParallelProcessingError, NotInitializedError)

File ~\anaconda3\Lib\site-packages\mlens\metrics_init_.py:10
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
7 Metric utilities and functions.
8 """
---> 10 from ..externals.sklearn.scorer import make_scorer
11 from .metrics import rmse, mape, wape
12 from .utils import assemble_table, assemble_data, Data

File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\scorer.py:33
31 from .. import six
32 from .base import is_regressor
---> 33 from .type_of_target import type_of_target
36 class _BaseScorer(six.with_metaclass(ABCMeta, object)):
37 def init(self, score_func, sign, kwargs):

File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\type_of_target.py:10
6 # Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
7 # License: BSD 3 clause
9 from future import division
---> 10 from collections import Sequence
13 from scipy.sparse import issparse
14 from scipy.sparse.base import spmatrix

ImportError: cannot import name 'Sequence' from 'collections'>>``