I'm using BigQueryML to train an XGBoost model on some of my data. When I create the model, I set the ENABLE_GLOBAL_EXPLAIN flag to TRUE, the model then trains properly and I can evaluate it. However there is no Interpretability tab on the model's page, and when I try to query the model with the ML.GLOBAL_EXPLAIN command, I get an error that says:
Invalid table-valued function ML.GLOBAL_EXPLAIN In function GLOBAL_EXPLAIN, the input model was not explained when it was created. at [4:3]
Is this a bug or am I doing something wrong?
Here's my create model code:
CREATE OR REPLACE MODEL `apteo-gcp.2539775073233929517.gb_prod_recos5`
OPTIONS(
INPUT_LABEL_COLS=['next_product_id'], -- label of future products purchased
MODEL_TYPE='BOOSTED_TREE_CLASSIFIER', -- gradient boosting using xgboost
CLASS_WEIGHTS=[STRUCT('gid://shopify/Product/6995522453704', 265),STRUCT('gid://shopify/Product/6995522355400', 265),STRUCT('gid://shopify/Product/6995522715848', 265),STRUCT('gid://shopify/Product/4448707969120', 100),STRUCT('gid://shopify/Product/6970658717896', 100),STRUCT('gid://shopify/Product/5688760467623', 100),STRUCT('gid://shopify/Product/4448711213152', 100),STRUCT('gid://shopify/Product/5430667804839', 100),STRUCT('gid://shopify/Product/5651893158055', 100),STRUCT('gid://shopify/Product/6995568918728', 125),STRUCT('gid://shopify/Product/4405707243616', 100),STRUCT('NO ORDER', 0.05)],
LEARN_RATE=0.15,
L2_REG=2.0,
L1_REG=1.5,
EARLY_STOP=TRUE,
MAX_ITERATIONS=75,
MIN_REL_PROGRESS=0.0001,
ENABLE_GLOBAL_EXPLAIN=TRUE,
DATA_SPLIT_METHOD="RANDOM"
)
AS
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