Few questions about `thresholds` parameter: This is what doc says "Param for Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values >= 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class' threshold."
0) How does threshold helps here? My general idea is if you have threshold 0.7 then at least one class prediction probability should be more then 0.7 if not then prediction should return empty. Means classify it as 'uncertain' . How can p/t function going to achieve that? 1) What probability it adjust? default column 'probability' is actually conditional probability and 'rawPrediction' confidence . I believe threshold will adjust 'rawPrediction' not 'probability' column. Am I right? 2) Here's how some of my probability and rawPrediction vector look like. How do I set threshold values based on this based on this? rawPrediction seems to be on log scale here. Probability: [2.233368649314982E-15,1.6429456680945863E-9,1.4377313514127723E-15,7.858651849363202E-15] rawPrediction: [-496.9606736723107,-483.452183395287,-497.40111830218746] Basically I want classifier to leave Prediction column empty if it doesn't have any probability that is more then 0.7 percent. Is there any default threshold like 0.5 ? if so on what values it applies cause "Probability" and "rawPrediction" don't seem to be between 0 and 1 -- [image: What's New with Xactly] <http://www.xactlycorp.com/email-click/> <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] <https://www.linkedin.com/company/xactly-corporation> [image: Twitter] <https://twitter.com/Xactly> [image: Facebook] <https://www.facebook.com/XactlyCorp> [image: YouTube] <http://www.youtube.com/xactlycorporation>
