Thanks a lot Sean. You are correct in assuming that my examples fall under a single category.
It is interesting to see that the posterior probability can actually be treated as something that is stable enough to have a constant threshold value on per class basis. It would, I assume, keep changing for a sample as I add/remove documents in the training set and thus warrant corresponding change in the threshold. Also, I have seen the class prediction probabilities to range from 0.003 to 0.8 for correct classifications in my sample data. This is a wide spectrum, so is there a way to change that? Maybe by replicating the samples for the classes I get low confidence but accurate classification for. Thanks, Jatin ----- Novice Big Data Programmer -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Naive-Baye-s-classification-confidence-tp19341p19358.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
