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1. Updating readme
snedamle Aug 25, 2021
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Update README.md
snedamle Sep 20, 2021
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16 changes: 14 additions & 2 deletions tribuo-classification/README.md
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Expand Up @@ -56,6 +56,14 @@ Micro Average | | | | |
Macro Average | | | | | 0.500 | 0.186 | 0.271|
Balanced Error Rate | | | | | 0.500

This sample demonstrates how you can integrate Tribuo and Conclave, to load and train a model. The model is evaluated based
off the testing data sent by the client. The evaluation result is sent back to the client, and we print it on the client's
screen.
This sample can be extended in a number of ways:
* The clients can tweak the model parameters, based off the evaluation result. The clients can then send
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@rusheb rusheb Sep 20, 2021

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This sample can be extended in a number of ways:
* The clients can tweak the model parameters, based off the evaluation result. The clients can then send
This sample can be extended in a number of ways:
* Enable the clients to tweak the model parameters, based off the evaluation result. The clients could then send

more training data to better train the model.
* The clients can further send out some input data, and the model can predict if the input data tumor is malignant or benign.
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* The clients can further send out some input data, and the model can predict if the input data tumor is malignant or benign.
* Enable the clients to send some input data once the model has been trained, to predict whether a tumor is malignant or benign.


## How to run on a non-linux/mac system

Start the host on a non-Linux system, which will build the enclave and host by default in simulation mode.
Expand All @@ -77,7 +85,7 @@ On other terminal, start a new client and pass in a new file name
You can start as many clients as you want. Pass in the file names each time. Once all the clients pass in the training data,
train the model inside the enclave and retrieve the evaluation result.

./gradlew client:run --args="EXECUTE <CONSTRAINT>"
./gradlew client:run --args="EVALUATE <CONSTRAINT>"

## How to run on a linux based system

Expand All @@ -100,12 +108,16 @@ On other terminal, start a new client and pass in a new file name
You can start as many clients as you want. Pass in the file names each time. Once all the clients pass in the training data,
train the model inside the enclave and retrieve the evaluation result.

./gradlew client:run --args="EXECUTE <CONSTRAINT>"
./gradlew client:run --args="EVALUATE <CONSTRAINT>"

To read more on Conclave go to the documentation site - https://docs.conclave.net


#### More about enclave constraint
The enclave constraint to be passed to the client arguments can be found printed during the build process as below:

Enclave code signer: AF89DF4211D742683C1CF940C78B7D5734CFAFA13EFAE65EC2A55643C0FE08CC

In this sample the `code signer` is used as enclave constraint, but you can also use the `code hash`. If you want to use it, remember to change the code of the client to:

`EnclaveConstraint.parse("C:"+ constraint +" SEC:INSECURE" ).check(attestation);`
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