diff --git a/.circleci/config.yml b/.circleci/config.yml index ef482f937..110f3e2ef 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -16,7 +16,7 @@ jobs: key: saved-cache - run: command: ./build_tools/circle/build_doc.sh - no_output_timeout: 40m + no_output_timeout: 30m - store_artifacts: path: doc/_build/html destination: doc diff --git a/examples/02_text_with_string_encoders.py b/examples/02_text_with_string_encoders.py index ab410309b..009a30382 100644 --- a/examples/02_text_with_string_encoders.py +++ b/examples/02_text_with_string_encoders.py @@ -209,8 +209,12 @@ def plot_box_results(named_results): # column in a dataframe. By default, |TextEncoder| uses the e5-small-v2 model. from skrub import TextEncoder +text_encoder = TextEncoder( + "sentence-transformers/paraphrase-albert-small-v2", + device="cpu", +) text_encoder_pipe = clone(gap_pipe).set_params( - **{"tablevectorizer__high_cardinality": TextEncoder()} + **{"tablevectorizer__high_cardinality": text_encoder} ) text_encoder_results = cross_validate(text_encoder_pipe, X, y, scoring="roc_auc") results.append(("TextEncoder", text_encoder_results)) diff --git a/examples/07_multiple_key_join.py b/examples/07_multiple_key_join.py index 24f9a88b2..7f93eedc5 100644 --- a/examples/07_multiple_key_join.py +++ b/examples/07_multiple_key_join.py @@ -47,9 +47,11 @@ from skrub.datasets import fetch_figshare +seed = 1 flights = fetch_figshare("41771418").X + # Sampling for faster computation. -flights = flights.sample(20_000, random_state=1, ignore_index=True) +flights = flights.sample(5_000, random_state=seed, ignore_index=True) flights.head() ############################################################################### @@ -85,7 +87,7 @@ weather = fetch_figshare("41771457").X # Sampling for faster computation. -weather = weather.sample(100_000, random_state=1, ignore_index=True) +weather = weather.sample(10_000, random_state=seed, ignore_index=True) weather.head() ######################################################################## @@ -164,10 +166,10 @@ ############################################################################### # The results: -from sklearn.model_selection import cross_val_score +from sklearn.model_selection import train_test_split -scores = cross_val_score(pipeline_hgb, X, y) -scores.mean() +X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=seed) +pipeline_hgb.fit(X_train, y_train).score(X_test, y_test) ############################################################################### # Conclusion @@ -177,4 +179,4 @@ # on imprecise and multiple-key correspondences. # This is made easy by skrub's |Joiner| transformer. # -# Our final cross-validated accuracy score is 0.58. +# Our final cross-validated accuracy score is 0.55. diff --git a/pixi.lock b/pixi.lock index eaf976854..f3853c190 100644 --- a/pixi.lock +++ b/pixi.lock @@ -1263,7 +1263,7 @@ environments: - 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