Yes, should be. It's also not necessarily nonnegative if you evaluate R^2 on a different data set than you fit it to. Is that the case?
On Tue, Sep 6, 2016 at 11:15 PM, Evan Zamir <zamir.e...@gmail.com> wrote: > I am using the default setting for setting fitIntercept, which *should* be > TRUE right? > > On Tue, Sep 6, 2016 at 1:38 PM Sean Owen <so...@cloudera.com> wrote: >> >> Are you not fitting an intercept / regressing through the origin? with >> that constraint it's no longer true that R^2 is necessarily >> nonnegative. It basically means that the errors are even bigger than >> what you'd get by predicting the data's mean value as a constant >> model. >> >> On Tue, Sep 6, 2016 at 8:49 PM, evanzamir <zamir.e...@gmail.com> wrote: >> > Am I misinterpreting what r2() in the LinearRegression Model summary >> > means? >> > By definition, R^2 should never be a negative number! >> > >> > >> > >> > -- >> > View this message in context: >> > http://apache-spark-user-list.1001560.n3.nabble.com/I-noticed-LinearRegression-sometimes-produces-negative-R-2-values-tp27667.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> > --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
