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
9003502
JSON
XML
RDF
Run 9003502
Task 146817 (Supervised Classification)
steel-plates-fault
Uploaded 09-04-2018 by
Hilde Weerts
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=hyperimp.utils.preprocessing.Condition alImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethre shold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sk learn.ensemble.forest.RandomForestClassifier)(1)
Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features
[]
sklearn.preprocessing.data.OneHotEncoder(17)_dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown
"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values
"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparse
true
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold
0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_bootstrap
false
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weight
null
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion
"entropy"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depth
null
sklearn.ensemble.forest.RandomForestClassifier(32)_max_features
0.3099278238035502
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodes
null
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease
0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_split
null
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf
2
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split
12
sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf
0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators
500
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs
1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_score
false
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state
1
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose
0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_start
false
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memory
null
hyperimp.utils.preprocessing.ConditionalImputer(1)_axis
0
hyperimp.utils.preprocessing.ConditionalImputer(1)_categorical_features
[]
hyperimp.utils.preprocessing.ConditionalImputer(1)_copy
true
hyperimp.utils.preprocessing.ConditionalImputer(1)_fill_empty
0
hyperimp.utils.preprocessing.ConditionalImputer(1)_missing_values
"NaN"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy
"mean"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy_nominal
"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer(1)_verbose
0
Result files
0 Evaluation measures