Hi Yes, I am using Survival Regression template from the PredictionIO site. I have understood quantile and prediction wrt. SR.
Thanks On Thu, Jul 27, 2017 at 11:16 PM, Mars Hall <[email protected]> wrote: > Hi Rasna, > > Folks here tend to respond to things they know about… I guess we don't > have a lot of experts for Survival Regression… I'll do my best to reply: > > > Are you using the Survival Regression template from the PredictionIO site? > > If so, we can see the exact algorithm in use is AFTSurvivalRegression: > https://github.com/goliasz/pio-template-sr/blob/master/ > src/main/scala/SRAlgorithm.scala#L47 > > Looking at the docs for that algo, > https://spark.apache.org/docs/latest/ml-classification- > regression.html#survival-regression > …the coefficients, intercept and scale are based on the model's fit to the > training data. Once the PredictionIO engine is trained, these will be > constant until trained with a different data set. > > The quantiles and prediction are the answers for each specific query > (transform). > > If you're seeking a deeper understanding of the prediction, I'm sorry but > I do not have that expertise! > > *Mars > > ( <> .. <> ) > > > On Jul 27, 2017, at 02:51, Rasna Tomar <[email protected]> wrote: > > > > Why there is no support for templates other than universal recommender.?? > > > > On Wed, Jul 19, 2017 at 3:20 PM, Rasna Tomar <[email protected]> > wrote: > > Hi All > > > > > > I am using survival regression for predicting whether user will purchase > in next few days or not. > > > > I am getting results similar to as shown below - > > > > Sample query - > > curl -i -X POST http://localhost:8000/queries.json > > -H "Content-Type: application/json" -d '{"features":[1.560,-0.605]}' > > > > > > Output - > > { > > "coefficients": [ > > -0.2633608588194104, > > 0.22152319227842276 > > ], > > "intercept": 2.6380946151040012, > > "prediction": 5.718979487634966, > > "quantiles": [ > > 1.1603238947151593, > > 4.995456010274735 > > ], > > "scale": 1.5472345574364683 > > > > } > > > > > > For each user I am getting same values coefficients, intercept and > scale, but Quantile and prediction values are different? > > What is the meaning of quantile and prediction here? > > > > Thanks > > > > > > > > > > > >
