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Run 9097166
Task 146824 (Supervised Classification)
mfeat-pixel
Uploaded 14-04-2018 by
Hilde Weerts
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sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=skl earn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_se lection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(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.preprocessing.data.StandardScaler(5)_copy
true
sklearn.preprocessing.data.StandardScaler(5)_with_mean
false
sklearn.preprocessing.data.StandardScaler(5)_with_std
true
sklearn.svm.classes.SVC(16)_C
464.57895299884603
sklearn.svm.classes.SVC(16)_cache_size
200
sklearn.svm.classes.SVC(16)_class_weight
null
sklearn.svm.classes.SVC(16)_coef0
0.2111826768686288
sklearn.svm.classes.SVC(16)_decision_function_shape
"ovr"
sklearn.svm.classes.SVC(16)_degree
3
sklearn.svm.classes.SVC(16)_gamma
0.0008563891817249367
sklearn.svm.classes.SVC(16)_kernel
"rbf"
sklearn.svm.classes.SVC(16)_max_iter
-1
sklearn.svm.classes.SVC(16)_probability
false
sklearn.svm.classes.SVC(16)_random_state
76810
sklearn.svm.classes.SVC(16)_shrinking
true
sklearn.svm.classes.SVC(16)_tol
0.0012696165189062523
sklearn.svm.classes.SVC(16)_verbose
false
hyperimp.utils.preprocessing.ConditionalImputer2(1)_axis
0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_categorical_features
[]
hyperimp.utils.preprocessing.ConditionalImputer2(1)_copy
true
hyperimp.utils.preprocessing.ConditionalImputer2(1)_fill_empty
0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_missing_values
"NaN"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy
"mean"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy_nominal
"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_verbose
0
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)_memory
null
Result files
0 Evaluation measures