You can serialize the model to a local/hdfs file system and use it later when you want.
Best Regards, Sonal Nube Technologies <http://www.nubetech.co> <http://in.linkedin.com/in/sonalgoyal> On Sat, Nov 1, 2014 at 12:02 AM, Sean Owen <so...@cloudera.com> wrote: > It sounds like you are asking about logistic regression, not linear > regression. If so, yes that's just what it does. The default would be > 0.5 in logistic regression. If you 'clear' the threshold you get the > raw margin out of this and other linear classifiers. > > On Fri, Oct 31, 2014 at 7:18 PM, Sameer Tilak <ssti...@live.com> wrote: > > Hi All, > > > > I am using LinearRegression and have a question about the details on > > model.predict method. Basically it is predicting variable y given an > input > > vector x. However, can someone point me to the documentation about what > is > > the threshold used in the predict method? Can that be changed ? I am > > assuming that i/p vector essentially gets mapped to a number and is > compared > > against a threshold value and then y is either set to 0 or 1 based on > those > > two numbers. > > > > Another question I have is if I want to save the model to hdfs for later > > reuse is there a recommended way for doing that? > > > > // Building the model > > val numIterations = 100 > > val model = LinearRegressionWithSGD.train(parsedData, numIterations) > > > > // Evaluate model on training examples and compute training error > > val valuesAndPreds = parsedData.map { point => > > val prediction = model.predict(point.features) > > (point.label, prediction) > > } > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
