sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona
lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklea
rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele
ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S
VC)(1) | Automatically created scikit-learn flow. |
openmlstudy14.preprocessing.ConditionalImputer(6)_axis | 0 |
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features | [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 20, 34, 36] |
openmlstudy14.preprocessing.ConditionalImputer(6)_copy | true |
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty | 0 |
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values | "NaN" |
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy | "median" |
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal | "most_frequent" |
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose | 0 |
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features | [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 20, 34, 36] |
sklearn.preprocessing.data.OneHotEncoder(18)_dtype | {"oml-python:serialized_object": "type", "value": "np.float64"} |
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown | "ignore" |
sklearn.preprocessing.data.OneHotEncoder(18)_n_values | "auto" |
sklearn.preprocessing.data.OneHotEncoder(18)_sparse | true |
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold | 0.0 |
sklearn.preprocessing.data.StandardScaler(6)_copy | true |
sklearn.preprocessing.data.StandardScaler(6)_with_mean | false |
sklearn.preprocessing.data.StandardScaler(6)_with_std | true |
sklearn.svm.classes.SVC(17)_C | 13794.551102713494 |
sklearn.svm.classes.SVC(17)_cache_size | 200 |
sklearn.svm.classes.SVC(17)_class_weight | null |
sklearn.svm.classes.SVC(17)_coef0 | -0.09363809979860527 |
sklearn.svm.classes.SVC(17)_decision_function_shape | null |
sklearn.svm.classes.SVC(17)_degree | 3 |
sklearn.svm.classes.SVC(17)_gamma | 0.0005862263664215184 |
sklearn.svm.classes.SVC(17)_kernel | "poly" |
sklearn.svm.classes.SVC(17)_max_iter | -1 |
sklearn.svm.classes.SVC(17)_probability | true |
sklearn.svm.classes.SVC(17)_random_state | 40857 |
sklearn.svm.classes.SVC(17)_shrinking | false |
sklearn.svm.classes.SVC(17)_tol | 0.007488755913871532 |
sklearn.svm.classes.SVC(17)_verbose | false |