Чтобы помочь понять проблему, вы можете запустить ниже
#standardSQL
SELECT
COUNTIF(weight_pounds IS NULL) weight_pounds_nulls,
COUNTIF(is_male IS NULL) is_male_nulls,
COUNTIF(gestation_weeks IS NULL) gestation_weeks_nulls,
COUNTIF(mother_age IS NULL) mother_age_nulls,
COUNTIF(mother_race IS NULL) mother_race_nulls
FROM (
SELECT
weight_pounds,
is_male,
gestation_weeks,
mother_age,
CAST(mother_race AS STRING) AS mother_race
FROM `bigquery-public-data.samples.natality`
WHERE weight_pounds IS NOT NULL
)
с результатом как
Row weight_pounds_nulls is_male_nulls gestation_weeks_nulls mother_age_nulls mother_race_nulls
1 0 0 4749775 0 9874846
Итак, бегите ниже вместо этого для ОЦЕНКИ
#standardSQL
SELECT
*
FROM
ML.EVALUATE(MODEL `bqml_tutorial.natality_model`,
(
SELECT
weight_pounds,
is_male,
gestation_weeks,
mother_age,
CAST(mother_race AS STRING) AS mother_race
FROM `bigquery-public-data.samples.natality`
WHERE weight_pounds IS NOT NULL
AND gestation_weeks IS NOT NULL
AND mother_race IS NOT NULL
))
так что будет ниже оценки
Row mean_absolute_error mean_squared_error mean_squared_log_error median_absolute_error r2_score explained_variance
1 0.957266870271064 1.6762698039982795 0.03411192361406951 0.73998132611964 0.047271288906207354 0.04732780918772106
И вы должны сделать ту же настройку для PREDICT, я думаю