ml_evaluator
Spark ML - Evaluators
A set of functions to calculate performance metrics for prediction models. Also see the Spark ML Documentation https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.ml.evaluation.package
Usage
ml_binary_classification_evaluator(x, label_col = "label",
raw_prediction_col = "rawPrediction", metric_name = "areaUnderROC",
uid = random_string("binary_classification_evaluator_"), ...)ml_binary_classification_eval(x, label_col = "label",
prediction_col = "prediction", metric_name = "areaUnderROC")
ml_multiclass_classification_evaluator(x, label_col = "label",
prediction_col = "prediction", metric_name = "f1",
uid = random_string("multiclass_classification_evaluator_"), ...)
ml_classification_eval(x, label_col = "label",
prediction_col = "prediction", metric_name = "f1")
ml_regression_evaluator(x, label_col = "label",
prediction_col = "prediction", metric_name = "rmse",
uid = random_string("regression_evaluator_"), ...)
Arguments
- x
A
spark_connection
object or atbl_spark
containing label and prediction columns. The latter should be the output ofsdf_predict
.- label_col
Name of column string specifying which column contains the true labels or values.
- raw_prediction_col
Name of column contains the scored probability of a success
- metric_name
The performance metric. See details.
- uid
A character string used to uniquely identify the ML estimator.
- ...
Optional arguments; currently unused.
- prediction_col
Name of the column that contains the predicted label or value NOT the scored probability. Column should be of type
Double
.
Details
The following metrics are supported
Binary Classification:
areaUnderROC
(default) orareaUnderPR
(not available in Spark 2.X.)Multiclass Classification:
f1
(default),precision
,recall
,weightedPrecision
,weightedRecall
oraccuracy
; for Spark 2.X:f1
(default),weightedPrecision
,weightedRecall
oraccuracy
.Regression:
rmse
(root mean squared error, default),mse
(mean squared error),r2
, ormae
(mean absolute error.)
ml_binary_classification_eval()
is an alias for ml_binary_classification_evaluator()
for backwards compatibility.
ml_classification_eval()
is an alias for ml_multiclass_classification_evaluator()
for backwards compatibility.
Value
The calculated performance metric