--- license: apache-2.0 library_name: sklearn tags: - tabular-classification - baseline-trainer --- ## Baseline Model trained on pruned_datavq__ydnj to apply classification on is_phishing **Metrics of the best model:** accuracy 1.0 average_precision 1.0 roc_auc 1.0 recall_macro 1.0 f1_macro 1.0 Name: DecisionTreeClassifier(class_weight='balanced', max_depth=1), dtype: float64 **See model plot below:**
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless id True False False ... False False False bad_domain False False False ... False True False safe_domain False False False ... False False False[3 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=1))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless id True False False ... False False False bad_domain False False False ... False True False safe_domain False False False ... False False False[3 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=1))])
EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless id True False False ... False False False bad_domain False False False ... False True False safe_domain False False False ... False False False[3 rows x 7 columns])
DecisionTreeClassifier(class_weight='balanced', max_depth=1)