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README.md

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@@ -22,14 +22,14 @@ Nowadays, the cost of computing many different models and hyperparameters is muc
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The models generated by automl-gs are intended to give a very strong *baseline* for solving a given problem; they're not the end-all-be-all that often accompanies the AutoML hype, but the resulting code is easily tweakable to improve from the baseline.
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You can view the hyperparameters and their values [here](automl_gs/hyperparameters.yml), and the metrics that can be optimized [here](automl_gs/metrics.yml)
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You can view the hyperparameters and their values [here](automl_gs/hyperparameters.yml), and the metrics that can be optimized [here](automl_gs/metrics.yml).
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## Framework Support
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Currently automl-gs supports the generation of models for regression and classification problems using the following Python frameworks:
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* TensorFlow (via `tf.keras`) | `tensorflow`
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* XGBoost (w/ hist method) | `xgboost`
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* XGBoost (w/ histogram binning) | `xgboost`
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To be implemented:
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