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Update flaml/automl.py

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Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
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2022-10-13 14:22:49 -04:00
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flaml/automl.py
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@@ -2405,7 +2405,23 @@ class AutoML(BaseEstimator):
e.g.,
skip_transform: boolean, default=False | Whether to pre-process data prior to modeling.
lexico_objectives: A dictionary with four elements.
lexico_objectives: dict, default=None | It specifics information needed to perform multi-objective
optimization with lexicographic preferences. When lexico_objectives it not None, flaml's AutoML uses "cfo"
as the `hpo_method`, which makes the input (if provided) `hpo_method' invalid. This dictionary shall
contain the following fields of key-value pairs:
- "metrics": a list of optimization objectives with the orders reflecting the priorities/preferences of the
objectives.
- "modes" (optional): a list of optimization modes (each mode either "min" or "max") corresponding to the
objectives in the metric list. If not provided, we use "min" as the default mode for all the objectives
"targets" (optional): a dictionary to specify the optimization targets on the objectives. The keys are the
metric names (provided in "metric"), and the values are the numerical target values.
- "tolerances"(optional): a dictionary to specify the optimality tolerances on objectives. The keys are the
metric names (provided in "metrics"), and the values are the numerical tolerances values.
E.g.,
```python
lexico_objectives = {"metrics":["error_rate","pred_time"], "modes":["min","min"],
"tolerances":{"error_rate":0.01,"pred_time":0.0}, "targets":{"error_rate":0.0}}
```
It specifics the information used for multiple objectives optimization with lexicographic preference.
e.g.,
```python