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docs: add snippet for creating boosted tree model #1142

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Nov 19, 2024
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docs: add snippet for creating boosted tree model #1142

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docs: create boosted tree model
rey-esp Nov 11, 2024
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merge main
rey-esp Nov 11, 2024
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Merge branch 'main' into b338872698-bigframes-v1
rey-esp Nov 12, 2024
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Merge branch 'main' into b338872698-bigframes-v1
rey-esp Nov 13, 2024
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Merge branch 'main' into b338872698-bigframes-v1
rey-esp Nov 14, 2024
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merge main
rey-esp Nov 14, 2024
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Merge branch 'main' into b338872698-bigframes-v1
rey-esp Nov 19, 2024
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update model
rey-esp Nov 19, 2024
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update test
rey-esp Nov 19, 2024
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26 changes: 25 additions & 1 deletion samples/snippets/classification_boosted_tree_model_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@


def test_boosted_tree_model(random_model_id: str) -> None:
# your_model_id = random_model_id
your_model_id = random_model_id
# [START bigquery_dataframes_bqml_boosted_tree_prepare]
import bigframes.pandas as bpd

Expand All @@ -39,4 +39,28 @@ def test_boosted_tree_model(random_model_id: str) -> None:
)
del input_data["functional_weight"]
# [END bigquery_dataframes_bqml_boosted_tree_prepare]
# [START bigquery_dataframes_bqml_boosted_tree_create]
from bigframes.ml import ensemble

# input_data is defined in an earlier step.
training_data = input_data[input_data["dataframe"] == "training"]
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No action needed, but something to consider for future: it would be nice to update the prepare section above to work without referencing an index (e.g. when ordering mode = "partial").

We have a few options, but the easiest will be to start with a string column and add (True, "training") as the last in the list of cases.

Aside: we have an issue open (349926559) to allow selecting any column in the dataframe (such as functional_weight, which would be a natural choice in this example) even if its a different type, so long as a True (default) case is provided.

X = training_data.drop(columns=["income_bracket", "dataframe"])
y = training_data["income_bracket"]
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Presumably you ran this code sample and it worked OK? I remember we had some bugs where y had to be a DataFrame not a Series in past, so just double-checking.

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The code sample seems to run! Not sure if I did it right so here's the colab: https://colab.sandbox.google.com/drive/10jA6zSRiptXWrTkCcmyCT_sYBjLqGJx0?resourcekey=0-0TrIkmDzAJw_F6ONFikwaA#scrollTo=wU367u1SAj3Y


# create and train the model
census_model = ensemble.XGBClassifier(
n_estimators=1,
booster="gbtree",
tree_method="hist",
max_iterations=1, # For a more accurate model, try 50 iterations.
subsample=0.85,
)
census_model.fit(X, y)

census_model.to_gbq(
your_model_id, # For example: "your-project.census.census_model"
replace=True,
)
# [END bigquery_dataframes_bqml_boosted_tree_create]
assert input_data is not None
assert census_model is not None