Edit model card

Baseline Model trained on irisg444_4c0 to apply classification on Species

Metrics of the best model:

accuracy 0.953333

recall_macro 0.953333

precision_macro 0.956229

f1_macro 0.953216

Name: LogisticRegression(class_weight='balanced', max_iter=1000), dtype: float64

See model plot below:

Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=               continuous  dirty_float  ...  free_string  useless

SepalLengthCm True False ... False False SepalWidthCm True False ... False False PetalLengthCm True False ... False False PetalWidthCm True False ... False False[4 rows x 7 columns])),('logisticregression',LogisticRegression(C=1, class_weight='balanced',max_iter=1000))])

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.

Disclaimer: This model is trained with dabl library as a baseline, for better results, use AutoTrain.

Logs of training including the models tried in the process can be found in logs.txt

Downloads last month
0
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.