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
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Citation
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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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