julien-c/skops-digits百度流畅ai制作
Model description
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Intended uses & limitations
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Training Procedure
Hyperparameters
The model is trained with below hyperparameters.免费的ai工具
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| Hyperparameter | Value |
|---|---|
| activation | relu |
| alpha | 0.0001 |
| batch_size | auto |
| beta_1 | 0.9 |
| beta_2 | 0.999 |
| early_stopping | False |
| epsilon | 1e-08 |
| hidden_layer_sizes | (100,) |
| learning_rate | constant |
| learning_rate_init | 0.001 |
| max_fun | 15000 |
| max_iter | 200 |
| momentum | 0.9 |
| n_iter_no_change | 10 |
| nesterovs_momentum | True |
| power_t | 0.5 |
| random_state | |
| shuffle | True |
| solver | adam |
| tol | 0.0001 |
| validation_fraction | 0.1 |
| verbose | False |
| warm_start | False |
Model Plot
The model plot is below.制作ai的软件
MLPClassifier()
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MLPClassifier()
How to Get Started with the Model
Use the code below to get started with the model.即梦al
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Model Card Authors
This model card is written by following authors:做al视频怎么赚钱
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Model Card Contact
You can contact the model card authors through following channels:
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Citation
Below you can find information related to citation.快问ai
BibTeX:即梦al
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数据统计
数据评估
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