metadata
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: pipeline_model_sklearn.joblib
widget:
- structuredData:
Age:
- 23
- 47
- 47
BP:
- HIGH
- LOW
- LOW
Cholesterol:
- HIGH
- HIGH
- HIGH
K:
- 0.031258
- 0.056468
- 0.068944
Na:
- 0.792535
- 0.739309
- 0.697269
Sex:
- F
- M
- M
Model description
[More Information Needed]
Intended uses & limitations
[More Information Needed]
Training Procedure
[More Information Needed]
Hyperparameters
Click to expand
Hyperparameter | Value |
---|---|
memory | |
steps | [('featureunion', FeatureUnion(transformer_list=[('float32_transform_139955258811312', Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[1, 2, 3])), ('compressstrings', CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []])), ('numpyreplacemissingvalues'... FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numimputer', NumImputer(missing_values=nan, strategy='median')), ('optstandardscaler', OptStandardScaler(use_scaler_flag=False)), ('float32_transform', float32_transform())]))])), ('numpypermutearray', NumpyPermuteArray(axis=0, permutation_indices=[1, 2, 3, 0, 4, 5])), ('lgbmclassifier', LGBMClassifier(class_weight='balanced', n_jobs=1, random_state=33))] |
verbose | False |
featureunion | FeatureUnion(transformer_list=[('float32_transform_139955258811312', Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[1, 2, 3])), ('compressstrings', CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []])), ('numpyreplacemissingvalues'... FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numimputer', NumImputer(missing_values=nan, strategy='median')), ('optstandardscaler', OptStandardScaler(use_scaler_flag=False)), ('float32_transform', float32_transform())]))]) |
numpypermutearray | NumpyPermuteArray(axis=0, permutation_indices=[1, 2, 3, 0, 4, 5]) |
lgbmclassifier | LGBMClassifier(class_weight='balanced', n_jobs=1, random_state=33) |
featureunion__n_jobs | |
featureunion__transformer_list | [('float32_transform_139955258811312', Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[1, 2, 3])), ('compressstrings', CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numpyreplaceunknown... 40061271003327253395033901872323469393]], missing_values_reference_list=['', '-', '?', nan])), ('boolean2float', boolean2float()), ('catimputer', CatImputer(missing_values=nan, strategy='most_frequent')), ('catencoder', CatEncoder(categories='auto', dtype=<class 'numpy.float64'>, encoding='ordinal', handle_unknown='error')), ('float32_transform', float32_transform())])), ('float32_transform_139955258809968', Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[0, 4, 5])), ('floatstr2float', FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numimputer', NumImputer(missing_values=nan, strategy='median')), ('optstandardscaler', OptStandardScaler(use_scaler_flag=False)), ('float32_transform', float32_transform())]))] |
featureunion__transformer_weights | |
featureunion__verbose | False |
featureunion__float32_transform_139955258811312 | Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[1, 2, 3])), ('compressstrings', CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numpyreplaceunknown... 40061271003327253395033901872323469393]], missing_values_reference_list=['', '-', '?', nan])), ('boolean2float', boolean2float()), ('catimputer', CatImputer(missing_values=nan, strategy='most_frequent')), ('catencoder', CatEncoder(categories='auto', dtype=<class 'numpy.float64'>, encoding='ordinal', handle_unknown='error')), ('float32_transform', float32_transform())]) |
featureunion__float32_transform_139955258809968 | Pipeline(steps=[('numpycolumnselector', NumpyColumnSelector(columns=[0, 4, 5])), ('floatstr2float', FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numimputer', NumImputer(missing_values=nan, strategy='median')), ('optstandardscaler', OptStandardScaler(use_scaler_flag=False)), ('float32_transform', float32_transform())]) |
featureunion__float32_transform_139955258811312__memory | |
featureunion__float32_transform_139955258811312__steps | [('numpycolumnselector', NumpyColumnSelector(columns=[1, 2, 3])), ('compressstrings', CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numpyreplaceunknownvalues', NumpyReplaceUnknownValues(filling_values=nan, filling_values_list=[nan, nan, nan], known_values_list=[[170172835760119224333519554008280666130, 140114708448418632577632402066430035116], [245397760256243238036686602120338271372, 87378989482499796866217412016778320776, 40061271003327253395033901872323469393], [245397760256243238036686602120338271372, 40061271003327253395033901872323469393]], missing_values_reference_list=['', '-', '?', nan])), ('boolean2float', boolean2float()), ('catimputer', CatImputer(missing_values=nan, strategy='most_frequent')), ('catencoder', CatEncoder(categories='auto', dtype=<class 'numpy.float64'>, encoding='ordinal', handle_unknown='error')), ('float32_transform', float32_transform())] |
featureunion__float32_transform_139955258811312__verbose | False |
featureunion__float32_transform_139955258811312__numpycolumnselector | NumpyColumnSelector(columns=[1, 2, 3]) |
featureunion__float32_transform_139955258811312__compressstrings | CompressStrings(compress_type='hash', dtypes_list=['char_str', 'char_str', 'char_str'], missing_values_reference_list=['', '-', '?', nan], misslist_list=[[], [], []]) |
featureunion__float32_transform_139955258811312__numpyreplacemissingvalues | NumpyReplaceMissingValues(missing_values=[]) |
featureunion__float32_transform_139955258811312__numpyreplaceunknownvalues | NumpyReplaceUnknownValues(filling_values=nan, filling_values_list=[nan, nan, nan], known_values_list=[[170172835760119224333519554008280666130, 140114708448418632577632402066430035116], [245397760256243238036686602120338271372, 87378989482499796866217412016778320776, 40061271003327253395033901872323469393], [245397760256243238036686602120338271372, 40061271003327253395033901872323469393]], missing_values_reference_list=['', '-', '?', nan]) |
featureunion__float32_transform_139955258811312__boolean2float | boolean2float() |
featureunion__float32_transform_139955258811312__catimputer | CatImputer(missing_values=nan, strategy='most_frequent') |
featureunion__float32_transform_139955258811312__catencoder | CatEncoder(categories='auto', dtype=<class 'numpy.float64'>, encoding='ordinal', handle_unknown='error') |
featureunion__float32_transform_139955258811312__float32_transform | float32_transform() |
featureunion__float32_transform_139955258811312__numpycolumnselector__columns | [1, 2, 3] |
featureunion__float32_transform_139955258811312__compressstrings__activate_flag | True |
featureunion__float32_transform_139955258811312__compressstrings__compress_type | hash |
featureunion__float32_transform_139955258811312__compressstrings__dtypes_list | ['char_str', 'char_str', 'char_str'] |
featureunion__float32_transform_139955258811312__compressstrings__missing_values_reference_list | ['', '-', '?', nan] |
featureunion__float32_transform_139955258811312__compressstrings__misslist_list | [[], [], []] |
featureunion__float32_transform_139955258811312__numpyreplacemissingvalues__filling_values | nan |
featureunion__float32_transform_139955258811312__numpyreplacemissingvalues__missing_values | [] |
featureunion__float32_transform_139955258811312__numpyreplaceunknownvalues__filling_values | nan |
featureunion__float32_transform_139955258811312__numpyreplaceunknownvalues__filling_values_list | [nan, nan, nan] |
featureunion__float32_transform_139955258811312__numpyreplaceunknownvalues__known_values_list | [[170172835760119224333519554008280666130, 140114708448418632577632402066430035116], [245397760256243238036686602120338271372, 87378989482499796866217412016778320776, 40061271003327253395033901872323469393], [245397760256243238036686602120338271372, 40061271003327253395033901872323469393]] |
featureunion__float32_transform_139955258811312__numpyreplaceunknownvalues__missing_values_reference_list | ['', '-', '?', nan] |
featureunion__float32_transform_139955258811312__boolean2float__activate_flag | True |
featureunion__float32_transform_139955258811312__catimputer__activate_flag | True |
featureunion__float32_transform_139955258811312__catimputer__missing_values | nan |
featureunion__float32_transform_139955258811312__catimputer__sklearn_version_family | 1 |
featureunion__float32_transform_139955258811312__catimputer__strategy | most_frequent |
featureunion__float32_transform_139955258811312__catencoder__activate_flag | True |
featureunion__float32_transform_139955258811312__catencoder__categories | auto |
featureunion__float32_transform_139955258811312__catencoder__dtype | <class 'numpy.float64'> |
featureunion__float32_transform_139955258811312__catencoder__encoding | ordinal |
featureunion__float32_transform_139955258811312__catencoder__handle_unknown | error |
featureunion__float32_transform_139955258811312__catencoder__sklearn_version_family | 1 |
featureunion__float32_transform_139955258811312__float32_transform__activate_flag | True |
featureunion__float32_transform_139955258809968__memory | |
featureunion__float32_transform_139955258809968__steps | [('numpycolumnselector', NumpyColumnSelector(columns=[0, 4, 5])), ('floatstr2float', FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[])), ('numpyreplacemissingvalues', NumpyReplaceMissingValues(missing_values=[])), ('numimputer', NumImputer(missing_values=nan, strategy='median')), ('optstandardscaler', OptStandardScaler(use_scaler_flag=False)), ('float32_transform', float32_transform())] |
featureunion__float32_transform_139955258809968__verbose | False |
featureunion__float32_transform_139955258809968__numpycolumnselector | NumpyColumnSelector(columns=[0, 4, 5]) |
featureunion__float32_transform_139955258809968__floatstr2float | FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'], missing_values_reference_list=[]) |
featureunion__float32_transform_139955258809968__numpyreplacemissingvalues | NumpyReplaceMissingValues(missing_values=[]) |
featureunion__float32_transform_139955258809968__numimputer | NumImputer(missing_values=nan, strategy='median') |
featureunion__float32_transform_139955258809968__optstandardscaler | OptStandardScaler(use_scaler_flag=False) |
featureunion__float32_transform_139955258809968__float32_transform | float32_transform() |
featureunion__float32_transform_139955258809968__numpycolumnselector__columns | [0, 4, 5] |
featureunion__float32_transform_139955258809968__floatstr2float__activate_flag | True |
featureunion__float32_transform_139955258809968__floatstr2float__dtypes_list | ['float_int_num', 'float_num', 'float_num'] |
featureunion__float32_transform_139955258809968__floatstr2float__missing_values_reference_list | [] |
featureunion__float32_transform_139955258809968__numpyreplacemissingvalues__filling_values | nan |
featureunion__float32_transform_139955258809968__numpyreplacemissingvalues__missing_values | [] |
featureunion__float32_transform_139955258809968__numimputer__activate_flag | True |
featureunion__float32_transform_139955258809968__numimputer__missing_values | nan |
featureunion__float32_transform_139955258809968__numimputer__strategy | median |
featureunion__float32_transform_139955258809968__optstandardscaler__use_scaler_flag | False |
featureunion__float32_transform_139955258809968__float32_transform__activate_flag | True |
numpypermutearray__axis | 0 |
numpypermutearray__permutation_indices | [1, 2, 3, 0, 4, 5] |
lgbmclassifier__boosting_type | gbdt |
lgbmclassifier__class_weight | balanced |
lgbmclassifier__colsample_bytree | 1.0 |
lgbmclassifier__importance_type | split |
lgbmclassifier__learning_rate | 0.1 |
lgbmclassifier__max_depth | -1 |
lgbmclassifier__min_child_samples | 20 |
lgbmclassifier__min_child_weight | 0.001 |
lgbmclassifier__min_split_gain | 0.0 |
lgbmclassifier__n_estimators | 100 |
lgbmclassifier__n_jobs | 1 |
lgbmclassifier__num_leaves | 31 |
lgbmclassifier__objective | |
lgbmclassifier__random_state | 33 |
lgbmclassifier__reg_alpha | 0.0 |
lgbmclassifier__reg_lambda | 0.0 |
lgbmclassifier__silent | warn |
lgbmclassifier__subsample | 1.0 |
lgbmclassifier__subsample_for_bin | 200000 |
lgbmclassifier__subsample_freq | 0 |
Model Plot
Pipeline(steps=[('featureunion',FeatureUnion(transformer_list=[('float32_transform_139955258811312',Pipeline(steps=[('numpycolumnselector',NumpyColumnSelector(columns=[1,2,3])),('compressstrings',CompressStrings(compress_type='hash',dtypes_list=['char_str','char_str','char_str'],missing_values_reference_list=['','-','?',nan],misslist_list=[[],[],[]...NumpyReplaceMissingValues(missing_values=[])),('numimputer',NumImputer(missing_values=nan,strategy='median')),('optstandardscaler',OptStandardScaler(use_scaler_flag=False)),('float32_transform',float32_transform())]))])),('numpypermutearray',NumpyPermuteArray(axis=0,permutation_indices=[1, 2, 3, 0, 4, 5])),('lgbmclassifier',LGBMClassifier(class_weight='balanced', n_jobs=1,random_state=33))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Pipeline(steps=[('featureunion',FeatureUnion(transformer_list=[('float32_transform_139955258811312',Pipeline(steps=[('numpycolumnselector',NumpyColumnSelector(columns=[1,2,3])),('compressstrings',CompressStrings(compress_type='hash',dtypes_list=['char_str','char_str','char_str'],missing_values_reference_list=['','-','?',nan],misslist_list=[[],[],[]...NumpyReplaceMissingValues(missing_values=[])),('numimputer',NumImputer(missing_values=nan,strategy='median')),('optstandardscaler',OptStandardScaler(use_scaler_flag=False)),('float32_transform',float32_transform())]))])),('numpypermutearray',NumpyPermuteArray(axis=0,permutation_indices=[1, 2, 3, 0, 4, 5])),('lgbmclassifier',LGBMClassifier(class_weight='balanced', n_jobs=1,random_state=33))])
FeatureUnion(transformer_list=[('float32_transform_139955258811312',Pipeline(steps=[('numpycolumnselector',NumpyColumnSelector(columns=[1,2,3])),('compressstrings',CompressStrings(compress_type='hash',dtypes_list=['char_str','char_str','char_str'],missing_values_reference_list=['','-','?',nan],misslist_list=[[],[],[]])),('numpyreplacemissingvalues'...FloatStr2Float(dtypes_list=['float_int_num','float_num','float_num'],missing_values_reference_list=[])),('numpyreplacemissingvalues',NumpyReplaceMissingValues(missing_values=[])),('numimputer',NumImputer(missing_values=nan,strategy='median')),('optstandardscaler',OptStandardScaler(use_scaler_flag=False)),('float32_transform',float32_transform())]))])
NumpyColumnSelector(columns=[1, 2, 3])
CompressStrings(compress_type='hash',dtypes_list=['char_str', 'char_str', 'char_str'],missing_values_reference_list=['', '-', '?', nan],misslist_list=[[], [], []])
NumpyReplaceMissingValues(missing_values=[])
NumpyReplaceUnknownValues(filling_values=nan,filling_values_list=[nan, nan, nan],known_values_list=[[170172835760119224333519554008280666130,140114708448418632577632402066430035116],[245397760256243238036686602120338271372,87378989482499796866217412016778320776,40061271003327253395033901872323469393],[245397760256243238036686602120338271372,40061271003327253395033901872323469393]],missing_values_reference_list=['', '-', '?', nan])
boolean2float()
CatImputer(missing_values=nan, strategy='most_frequent')
CatEncoder(categories='auto', dtype=<class 'numpy.float64'>, encoding='ordinal',handle_unknown='error')
float32_transform()
NumpyColumnSelector(columns=[0, 4, 5])
FloatStr2Float(dtypes_list=['float_int_num', 'float_num', 'float_num'],missing_values_reference_list=[])
NumpyReplaceMissingValues(missing_values=[])
NumImputer(missing_values=nan, strategy='median')
OptStandardScaler(use_scaler_flag=False)
float32_transform()
NumpyPermuteArray(axis=0, permutation_indices=[1, 2, 3, 0, 4, 5])
LGBMClassifier(class_weight='balanced', n_jobs=1, random_state=33)
Evaluation Results
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How to Get Started with the Model
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Model Card Authors
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Citation
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BibTeX:
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model_card_authors
wenpei
model_description
test propose for autoai and hugging face