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wendell-yu-2024
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secord-model

Tabular Classification
Scikit-learn
Joblib
skops
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Model description

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Intended uses & limitations

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Training Procedure

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Hyperparameters

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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))])
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model_card_authors

wenpei

model_description

test propose for autoai and hugging face

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