I finally solved the problem by following code
var m: org.apache.spark.mllib.classification.LogisticRegressionModel = null
m = newModel // newModel is the loaded one, see above post of mine
val labelsAndPredsOnGoodData = goodDataPoints.map { point =>
val prediction = m.predict(point.features)
(point.label, prediction)
} // this works!
Thanks Shixiong for his heuristic codes which lead me to this solution.
btw, accoring to this git commit
<https://www.mail-archive.com/commits@spark.apache.org/msg01988.html> ,
private[mllib] will be removed from linear models' constructors,"This is
part of SPARK-2495 to allow users construct linear models manually"
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