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Feature/sof 2002 #24
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example/job/ml_model.json
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Example ML model schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for model is modified to include ML models https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-d9fa058c7568fad2c154cae5ae1b8679
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{ |
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Example ML workflow schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for workflow is not modified
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Example ML unit (fit) schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for unit is modified to include ML units
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-9b527677fbdc8781894e1d6a76da0c70
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{ |
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Example ML unit (interface) schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for unit is modified to include ML units
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-9b527677fbdc8781894e1d6a76da0c70
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{ |
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Example ML unit (predict) schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for unit is modified to include ML units
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-9b527677fbdc8781894e1d6a76da0c70
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{ |
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Example ML Fit unit schema.
Schema for ML fit unit:
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-18e22f7533d5a7e5997661e9e419bfdb
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{ |
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Example ML Interface unit schema.
Schema for ML interface unit:
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-4567c3822b8d8d23ac825eef93b79701
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{ |
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Example ML Predict unit schema.
Schema for ML predict unit:
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-ef0d5749eee2b35a8de655f657f0e261
example/job/model/ml_method.json
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Example method schema. A file is added here with prefix "ml_" to show an example.
The existing JSON schema for method is modified to include ML methods
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-01d16ed8967fedca6691f225bbccf127
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"{\"Si\":{\"c8zG3XcnnTybfP3QQ\":0.6875,\"wWK2XCyivQrG8j34Z\":0.8125},\"Ge\":{\"c8zG3XcnnTybfP3QQ\":0.3125,\"wWK2XCyivQrG8j34Z\":0.1875},\"lattice_volume\":{\"c8zG3XcnnTybfP3QQ\":327.1127749111,\"wWK2XCyivQrG8j34Z\":327.1127749111}}" |
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Example input data for model training. This data is also stored with the trained model
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Example model parameters schema.
Schema for storing model parameters
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-77399703a8199ad7ffdb54ee71260074
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Example schema for prediction in ML. Prediction is a type of ML method.
Prediction schema is here:
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-8f2aae9a6d339d59c0de7032d64e2e32
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Example schema for precision of a method in ML.
Precision schema is here:
https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-4bcd9a4659d8983393149071d7c2d416
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ML Fit unit schema
Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-8640cd78ecf402e276ec40dab50a3d1f
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ML interface unit schema
Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-e94cf4cd5e2adb4e9bc8a1d1c6159b70
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{ |
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ML Predict unit schema
Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-61665cbffe489c45dafd64cd422c37fc
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{ |
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ML Transform unit schema. No example.
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{ |
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Classification is a type of ML method. No example
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Precision of ML method (type: classification). No Example
schema/job/theory/ml/prediction.json
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Prediction is a type of ML method. Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-39813d9642bb6ee3939bb4d5002fbc4c
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{ |
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Precision of ML method (type: Prediction).
Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-f2be34f62401c4f2156ac65acf497437
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{ |
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Schema for storing model parameters.
Example is here: https://github.com/Exabyte-io/exabyte-materials-json/pull/24/files#diff-9612b97f18df07de17543eb3eea5abf8
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"{\"Si\":{\"c8zG3XcnnTybfP3QQ\":0.6875,\"wWK2XCyivQrG8j34Z\":0.8125},\"Ge\":{\"c8zG3XcnnTybfP3QQ\":0.3125,\"wWK2XCyivQrG8j34Z\":0.1875},\"lattice_volume\":{\"c8zG3XcnnTybfP3QQ\":327.1127749111,\"wWK2XCyivQrG8j34Z\":327.1127749111}}" |
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We need to make it into a proper JSON object as discussed
], | ||
"intercept": 0.45, | ||
"modelData" : { | ||
"...": "(include(input_data)" |
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Extra braces - did you test this?
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