8918
6892
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)
sklearn.pipeline.Pipeline
2
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-17T18:43:04
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
memory
null
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
columntransformer
8891
6892
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))
sklearn.compose._column_transformer.ColumnTransformer
3
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
n_jobs
null
remainder
"passthrough"
sparse_threshold
0.3
transformer_weights
null
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3]}}]
numeric
8892
6892
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)
sklearn.pipeline.Pipeline
3
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
memory
null
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
imputer
8893
6892
sklearn.preprocessing.imputation.Imputer
sklearn.preprocessing.imputation.Imputer
34
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
axis
0
copy
true
missing_values
"NaN"
strategy
"median"
verbose
0
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
standardscaler
8894
6892
sklearn.preprocessing.data.StandardScaler
sklearn.preprocessing.data.StandardScaler
20
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
copy
true
with_mean
true
with_std
true
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
nominal
8895
6892
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)
sklearn.pipeline.Pipeline
3
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
memory
null
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
simpleimputer
8896
6892
sklearn.impute.SimpleImputer
sklearn.impute.SimpleImputer
6
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
copy
true
fill_value
-1
missing_values
NaN
strategy
"constant"
verbose
0
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
onehotencoder
8897
6892
sklearn.preprocessing._encoders.OneHotEncoder
sklearn.preprocessing._encoders.OneHotEncoder
6
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
categorical_features
null
categories
null
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
handle_unknown
"ignore"
n_values
null
sparse
true
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
variancethreshold
8898
6892
sklearn.feature_selection.variance_threshold.VarianceThreshold
sklearn.feature_selection.variance_threshold.VarianceThreshold
21
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-05T00:58:40
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
threshold
0.0
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
randomforestclassifier
8919
6892
sklearn.ensemble.forest.RandomForestClassifier
sklearn.ensemble.forest.RandomForestClassifier
48
openml==0.8.0dev,sklearn==0.20.2
Automatically created scikit-learn flow.
2019-01-17T18:43:04
English
sklearn==0.20.2
numpy>=1.6.1
scipy>=0.9
bootstrap
false
class_weight
null
criterion
"gini"
max_depth
null
max_features
0.267441246822437
max_leaf_nodes
null
min_impurity_decrease
0.0
min_impurity_split
null
min_samples_leaf
6
min_samples_split
7
min_weight_fraction_leaf
0.0
n_estimators
100
n_jobs
null
oob_score
false
random_state
null
verbose
0
warm_start
false
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2
openml-python
python
scikit-learn
sklearn
sklearn_0.20.2