Probabilities won't sum to 1 since this expression doesn't incorporate the probability of the evidence, I imagine? it's constant across classes so is usually excluded. It would appear as a "- log(P(evidence))" term.
On Tue, Dec 2, 2014 at 10:44 AM, MariusFS <marius.fete...@sien.com> wrote: > Are we sure that exponentiating will give us the probabilities? I did some > tests by cloning the MLLIb class and adding the required code but the > calculated probabilities do not add up to 1. > > I tried something like : > > def predictProbs(testData: Vector): (BDV[Double], BDV[Double]) = { > val logProbs = brzPi + brzTheta * new BDV[Double](testData.toArray) > val probs = logProbs.map(x => math.exp(x)) > (logProbs, probs) > } > > This was because I need the actual probs to process downstream from this... > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/MLlib-Naive-Bayes-classifier-confidence-tp18456p20175.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org