YAML Metadata
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Model description
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Intended uses & limitations
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Training Procedure
Hyperparameters
The model is trained with below hyperparameters.
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| Hyperparameter | Value |
|---|---|
| C | 1.0 |
| class_weight | |
| dual | False |
| fit_intercept | True |
| intercept_scaling | 1 |
| l1_ratio | |
| max_iter | 100 |
| multi_class | auto |
| n_jobs | |
| penalty | l2 |
| random_state | 0 |
| solver | lbfgs |
| tol | 0.0001 |
| verbose | 0 |
| warm_start | False |
Model Plot
The model plot is below.
LogisticRegression(random_state=0)Please rerun this cell to show the HTML repr or trust the notebook.
LogisticRegression(random_state=0)
Evaluation Results
You can find the details about evaluation process and the evaluation results.
| Metric | Value |
|---|---|
| Train Accuracy | 0.791531 |
| Test Accuracy | 0.714286 |
How to Get Started with the Model
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Model Card Authors
This model card is written by following authors:
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Model Card Contact
You can contact the model card authors through following channels: [More Information Needed]
Citation
Below you can find information related to citation.
BibTeX:
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limitations
Mô hình chưa thể dùng trong production.
model_description
Regression model thử nghiệm với skops.
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