Run
OpenML
Help
Sign in
×
Sign in
No account? Join OpenML
Forgot password
×
JavaScript is required to properly view the contents of this page!
OpenML
Explore
Data
Task
Flow
Run
Study
Task type
Measure
People
Help
Blog
Contact
Please cite us
5937978
JSON
XML
RDF
Run 5937978
Task 3543 (Supervised Classification)
irish
Uploaded 14-07-2017 by
Jan van Rijn
0 likes
downloaded by 0 people
0 issues
0 downvotes
, 0 total downloads
Evaluation Engine Exception: Run description file not present.
Add tag
Issue
#Downvotes for this reason
By
Flow
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.forest.RandomForestClassifier)(1)
Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(21)_bootstrap
true
sklearn.ensemble.forest.RandomForestClassifier(21)_class_weight
null
sklearn.ensemble.forest.RandomForestClassifier(21)_criterion
"entropy"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depth
null
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features
0.8862132365961809
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodes
null
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split
1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf
5
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split
9
sklearn.ensemble.forest.RandomForestClassifier(21)_min_weight_fraction_leaf
0.0
sklearn.ensemble.forest.RandomForestClassifier(21)_n_estimators
100
sklearn.ensemble.forest.RandomForestClassifier(21)_n_jobs
1
sklearn.ensemble.forest.RandomForestClassifier(21)_oob_score
false
sklearn.ensemble.forest.RandomForestClassifier(21)_random_state
58885
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose
0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_start
false
openmlstudy14.preprocessing.ConditionalImputer(2)_axis
0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features
[0, 2, 4]
openmlstudy14.preprocessing.ConditionalImputer(2)_copy
true
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty
0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values
"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy
"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal
"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose
0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features
[0, 2, 4]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown
"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values
"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparse
false
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold
0.0
Result files
0 Evaluation measures