2652610018@qq.com
3 years ago
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| @@ -71,7 +71,7 @@ In our sklearn digits classification example, these would be (64,) and (10,) res | |||||
| To accurately and effectively match users with appropriate learnwares for their tasks, we require information about your training dataset. | To accurately and effectively match users with appropriate learnwares for their tasks, we require information about your training dataset. | ||||
| Specifically, you are required to provide a statistical specification | Specifically, you are required to provide a statistical specification | ||||
| stored as a json file, such as ``stat.json``, which contains the statistical information of the dataset. | stored as a json file, such as ``stat.json``, which contains the statistical information of the dataset. | ||||
| This json file meets all our requirements regarding your training data, so you don't need to upload the actual data. | |||||
| This json file meets all our requirements regarding your training data, so you don't need to upload the local original data. | |||||
| There are various methods to generate a statistical specification. | There are various methods to generate a statistical specification. | ||||
| If you choose to use Reduced Kernel Mean Embedding (RKME) as your statistical specification, | If you choose to use Reduced Kernel Mean Embedding (RKME) as your statistical specification, | ||||
| @@ -85,6 +85,9 @@ the following code snippet offers guidance on how to construct and store the RKM | |||||
| spec = specification.utils.generate_rkme_spec(X=data_X) | spec = specification.utils.generate_rkme_spec(X=data_X) | ||||
| spec.save("stat.json") | spec.save("stat.json") | ||||
| Significantly, the RKME generation process is entirely conducted on your local machine, without any involvement of cloud services, | |||||
| guaranteeing the security and privacy of your local original data. | |||||
| ``learnware.yaml`` | ``learnware.yaml`` | ||||
| ------------------ | ------------------ | ||||