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	[('preprocessor', TextPreprocessor()), ('tfidf', TfidfVectorizer(max_features=2000, min_df=2, ngram_range=(1, 2))), ('classifier', XGBClassifier(base_score=None, booster=None, callbacks=None, colsample_bylevel=None, colsample_bynode=None, colsample_bytree=None, device=None, early_stopping_rounds=None, enable_categorical=False, eval_metric='mlogloss', feature_types=None, gamma=None, grow_policy=None, importance_type=None, interaction_constraints=None, learning_rate=None, max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None, max_delta_step=None, max_depth=None, max_leaves=None, min_child_weight=None, missing=nan, monotone_constraints=None, multi_strategy=None, n_estimators=None, n_jobs=None, num_class=8, num_parallel_tree=None, ...))]
verbose	False
preprocessor	TextPreprocessor()
tfidf	TfidfVectorizer(max_features=2000, min_df=2, ngram_range=(1, 2))
classifier	XGBClassifier(base_score=None, booster=None, callbacks=None, colsample_bylevel=None, colsample_bynode=None, colsample_bytree=None, device=None, early_stopping_rounds=None, enable_categorical=False, eval_metric='mlogloss', feature_types=None, gamma=None, grow_policy=None, importance_type=None, interaction_constraints=None, learning_rate=None, max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None, max_delta_step=None, max_depth=None, max_leaves=None, min_child_weight=None, missing=nan, monotone_constraints=None, multi_strategy=None, n_estimators=None, n_jobs=None, num_class=8, num_parallel_tree=None, ...)
tfidf__analyzer	word
tfidf__binary	False
tfidf__decode_error	strict
tfidf__dtype	<class 'numpy.float64'>
tfidf__encoding	utf-8
tfidf__input	content
tfidf__lowercase	True
tfidf__max_df	1.0
tfidf__max_features	2000
tfidf__min_df	2
tfidf__ngram_range	(1, 2)
tfidf__norm	l2
tfidf__preprocessor
tfidf__smooth_idf	True
tfidf__stop_words
tfidf__strip_accents
tfidf__sublinear_tf	False
tfidf__token_pattern	(?u)\b\w\w+\b
tfidf__tokenizer
tfidf__use_idf	True
tfidf__vocabulary
classifier__objective	multi:softmax
classifier__base_score
classifier__booster
classifier__callbacks
classifier__colsample_bylevel
classifier__colsample_bynode
classifier__colsample_bytree
classifier__device
classifier__early_stopping_rounds
classifier__enable_categorical	False
classifier__eval_metric	mlogloss
classifier__feature_types
classifier__gamma
classifier__grow_policy
classifier__importance_type
classifier__interaction_constraints
classifier__learning_rate
classifier__max_bin
classifier__max_cat_threshold
classifier__max_cat_to_onehot
classifier__max_delta_step
classifier__max_depth
classifier__max_leaves
classifier__min_child_weight
classifier__missing	nan
classifier__monotone_constraints
classifier__multi_strategy
classifier__n_estimators
classifier__n_jobs
classifier__num_parallel_tree
classifier__random_state	42
classifier__reg_alpha
classifier__reg_lambda
classifier__sampling_method
classifier__scale_pos_weight
classifier__subsample
classifier__tree_method
classifier__validate_parameters
classifier__verbosity
classifier__num_class	8

Model Plot

Pipeline(steps=[('preprocessor', TextPreprocessor()),('tfidf',TfidfVectorizer(max_features=2000, min_df=2,ngram_range=(1, 2))),('classifier',XGBClassifier(base_score=None, booster=None, callbacks=None,colsample_bylevel=None, colsample_bynode=None,colsample_bytree=None, device=None,early_stopping_rounds=None,enable_categorical=False, eval_metric='mlogloss',feature_types=None, gamma=None, grow_policy=None,importance_type=None,interaction_constraints=None, learning_rate=None,max_bin=None, max_cat_threshold=None,max_cat_to_onehot=None, max_delta_step=None,max_depth=None, max_leaves=None,min_child_weight=None, missing=nan,monotone_constraints=None, multi_strategy=None,n_estimators=None, n_jobs=None, num_class=8,num_parallel_tree=None, ...))])

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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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limitations

This model is a poor performing XGBClassifier for test upload purpose

model_card_author

theterryzhang

model_description

This model does some basic text processing (lower, lemmatize), TF-IDF vectorize and then fits an XGBoostClassifier