Hello,
I'm working with the ML package for regression purposes and I get good
results on my data.
I'm now trying to get multiple metrics at once, as right now, I'm doing
what is suggested by the examples here:
https://spark.apache.org/docs/2.1.0/ml-classification-regression.html
Basically the code in the examples is this:
val evaluator = new RegressionEvaluator()
.setLabelCol("label")
.setPredictionCol("prediction")
.setMetricName("rmse")
val rmse = evaluator.evaluate(predictions)
This gives me the RMSE for my test data which is fine, but I'm also
interested in MSE, MAE, MAPE, Rsquare and Qsquare
I thus looked at the documentation here:
https://spark.apache.org/docs/2.1.0/api/java/org/apache/spark/ml/evaluation/RegressionEvaluator.html#metricName%28%29
where I see that I can get RMSE, MSE, MAE and Rsquare but it does not
appear that I can get them computed all at once, going over the data
rows only once and not 5 times as the example code would suggest it is
needed to do so.
How can I achieve that single pass computation?
Then, there are MAPE and Qsquare missing, how can I get those computed
as well, ideally while computing the 4 others?
Regards
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