Can you post the final iteration of the model? Also the expression you used to train the model?
How much training data do you have? Ho many positive examples and negatives examples? Joel Bernstein http://joelsolr.blogspot.com/ On Tue, Feb 7, 2017 at 2:14 PM, Susheel Kumar <susheel2...@gmail.com> wrote: > Hello, > > I am tried to follow http://joelsolr.blogspot.com/ to see if we can > classify positive & negative feedbacks using streaming expressions. All > works but end result where probability_d result of classify expression > gives similar results for positive / negative feedback. See below > > What I may be missing here. Do i need to put more data in training set or > something else? > > > { "result-set": { "docs": [ { "body_txt": [ "love the company" ], > "score_d": 2.1892474120319667, "id": "6", "probability_d": > 0.977944433135261 }, { "body_txt": [ "bad experience " ], "score_d": > 3.1689453250842914, "id": "5", "probability_d": 0.9888109278133054 }, { > "body_txt": [ "This company rewards its employees, but you should only work > here if you truly love sales. The stress of the job can get to you and they > definitely push you." ], "score_d": 4.621702323888672, "id": "4", > "probability_d": 0.9999999999898557 }, { "body_txt": [ "no chance for > advancement with that company every year I was there it got worse I don't > know if all branches of adp but Florence organization was turn over rate > would be higher if it was for temp workers" ], "score_d": > 5.288898825826228, "id": "3", "probability_d": 0.9999999999999956 }, { > "body_txt": [ "It was a pleasure to work at the Milpitas campus. The team > that works there are professional and dedicated individuals. The level of > loyalty and dedication is impressive" ], "score_d": 2.5303947056922937, > "id": "2", "probability_d": 0.9999990430778418 }, >
