Modelpublic

scikit-learn/tabular-playground

sourceHugging Faceupdated 4y agoView on Hugging Face

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Model Card

Model description

This is a DecisionTreeClassifier model built for Kaggle Tabular Playground Series August 2022, trained on supersoaker production failures dataset.

Intended uses & limitations

This model is not ready to be used in production.

Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

<details> <summary> Click to expand </summary>

Hyperparameter	Value
memory
steps	[('transformation', ColumnTransformer(transformers=[('loadingmissingvalueimputer', SimpleImputer(), ['loading']), ('numericalmissingvalueimputer', SimpleImputer(),['loading', 'measurement3', 'measurement4','measurement5', 'measurement6','measurement7', 'measurement8','measurement9', 'measurement10','measurement11', 'measurement12','measurement13', 'measurement14','measurement15', 'measurement16','measurement17']),('attribute0encoder', OneHotEncoder(),['attribute0']),('attribute1encoder', OneHotEncoder(),['attribute1']),('productcodeencoder', OneHotEncoder(),['productcode'])])), ('model', DecisionTreeClassifier(max_depth=4))]
verbose	False
transformation	ColumnTransformer(transformers=[('loadingmissingvalueimputer',SimpleImputer(), ['loading']),('numericalmissingvalueimputer',SimpleImputer(),['loading', 'measurement3', 'measurement4','measurement5', 'measurement6','measurement7', 'measurement8','measurement9', 'measurement10','measurement11', 'measurement12','measurement13', 'measurement14','measurement15', 'measurement16','measurement17']),('attribute0encoder', OneHotEncoder(),['attribute0']),('attribute1encoder', OneHotEncoder(),
'attribute1']),('productcodeencoder', OneHotEncoder(),['productcode'])])
model	DecisionTreeClassifier(max_depth=4)
transformation_njobs
transformation__remainder	drop
transformation_sparsethreshold	0.3
transformation_transformerweights
transformation__transformers	[('loadingmissingvalueimputer', SimpleImputer(), ['loading']), ('numericalmissingvalueimputer', SimpleImputer(), ['loading', 'measurement3', 'measurement4', 'measurement5', 'measurement6', 'measurement7', 'measurement8', 'measurement9', 'measurement10', 'measurement11', 'measurement12', 'measurement13', 'measurement14', 'measurement15', 'measurement16', 'measurement17']), ('attribute0encoder', OneHotEncoder(), ['attribute0']), ('attribute1encoder', OneHotEncoder(), ['attribute1']), ('productcodeencoder', OneHotEncoder(),['productcode'])]

transformation__verbose	False
transformation_verbosefeaturenamesout	True
transformation_loadingmissingvalueimputer	SimpleImputer()
transformation_numericalmissingvalueimputer	SimpleImputer()
transformation_attribute0_encoder	OneHotEncoder()
transformation_attribute1_encoder	OneHotEncoder()
transformation_productcode_encoder	OneHotEncoder()
transformation_loadingmissingvalueimputer_addindicator	False
transformation_loadingmissingvalueimputer__copy	True
transformation_loadingmissingvalueimputer_fillvalue
transformation_loadingmissingvalueimputer_missingvalues	nan
transformation_loadingmissingvalueimputer__strategy	mean
transformation_loadingmissingvalueimputer__verbose	0
transformation_numericalmissingvalueimputer_addindicator	False
transformation_numericalmissingvalueimputer__copy	True
transformation_numericalmissingvalueimputer_fillvalue
transformation_numericalmissingvalueimputer_missingvalues	nan
transformation_numericalmissingvalueimputer__strategy	mean
transformation_numericalmissingvalueimputer__verbose	0
transformation_attribute0encoder_categories	auto
transformation_attribute0encoder_drop
transformation_attribute0encoder_dtype	<class 'numpy.float64'>
transformation_attribute0encoderhandleunknown	error
transformation_attribute0encoder_sparse	True
transformation_attribute1encoder_categories	auto
transformation_attribute1encoder_drop
transformation_attribute1encoder_dtype	<class 'numpy.float64'>
transformation_attribute1encoderhandleunknown	error
transformation_attribute1encoder_sparse	True
transformation_productcodeencoder_categories	auto
transformation_productcodeencoder_drop
transformation_productcodeencoder_dtype	<class 'numpy.float64'>
transformation_productcodeencoderhandleunknown	error
transformation_productcodeencoder_sparse	True
model_ccpalpha	0.0
model_classweight
model__criterion	gini
model_maxdepth	4
model_maxfeatures
model_maxleaf_nodes
model_minimpurity_decrease	0.0
model_minsamples_leaf	1
model_minsamples_split	2
model_minweightfractionleaf	0.0
model_randomstate
model__splitter	best

</details>

Model Plot

The model plot is below.

Evaluation Results

You can find the details about evaluation process and the evaluation results.

Metric	Value
accuracy	0.7888
f1 score	0.7888

How to Get Started with the Model

Use the code below to get started with the model.

<details> <summary> Click to expand </summary>

python

import pickle 
with open(decision-tree-playground-kaggle/model.pkl, 'rb') as file: 
    clf = pickle.load(file)

</details>

Model Card Authors

This model card is written by following authors:

huggingface

Model Card Contact

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Citation

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BibTeX:

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Tree Plot [image]

Confusion Matrix [image]