Generic shapely values #26
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lantiga
approved these changes
Sep 21, 2021
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "In this example we develop a small fraud detection model for credit card transactions based on XGBoost, export it to TorchScript using Hummingbird (https://github.com/microsoft/hummingbird) and run Shapley Value Sampling explanations (see https://captum.ai/api/shapley_value_sampling.html for reference) on it, also exported to TorchScript.\n", |
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I would change the description, since now the journey is different
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We are interested to explore are casesof fraud, so we extract them from the test set." |
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Typos: "We are interested to explore cases of fraud"
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "At this point we can load the models we exported into RedisAI and serve them from there. After making sure RedisAI is running, we initialize the client." |
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Update text to reflect the fact that the explainer is a script now.
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We read the model and the explainer from the saved TorchScript." |
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We load both models into RedisAI." |
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "All, set, it's now test time. We reuse our `X_test_fraud` NumPy array we created previously. We set it, run both models, and get predictions and explanations as arrays." |
| n_samples = int(args[0]) | ||
| number_of_outputs = int(args[1]) | ||
| output_tensor_index = int(args[2]) | ||
| if(len(args)==4): |
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formatting
if len(args) == 4:
lantiga
reviewed
Sep 22, 2021
| "metadata": {}, | ||
| "source": [ | ||
| "We load both models into RedisAI." | ||
| "We load both movel and script into RedisAI." |
lantiga
approved these changes
Sep 22, 2021
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