Hi all,
I have applied Random Forest on my data and divided data into test and rain set
to see the prediction results and it seems good cause the accuracy is 82%. Now
my question is how can I plot MDS on predicted data? here is my code:
spl=sample.split(df$PatientType,SplitRatio = 0.7)
Train=subset(df,spl==TRUE)
Test=subset(df,spl==FALSE)
SecondTree=randomForest(PatientType~ cookie + curtains + get + mother +
overflowing + sink +thats + window + stool + heres + drying + chair + okay
+outside + standing + tipping + windows + blowing + breeze +counter + finger +
onto + open + reaching + didnt + spilled +action + quiet + summer + mouth +
puddle + good + wind +whos + sort,data =
Train,nodesize=25,ntree=200,proximity=TRUE)
PredictForest=predict(SecondTree,newdata =Test)
Is MDS plot a way to find out if the classification are easy to be separated?
thanks for any help.
Elahe
Elahe: On Thu, May 25, 2017 at 8:15 AM, Elahe chalabi via R-help <r-help at r-project.org> wrote:> Hi all, > I have applied Random Forest on my data and divided data into test and rain set to see the prediction results and it seems good cause the accuracy is 82%. Now my question is how can I plot MDS on predicted data? here is my code: > > > > spl=sample.split(df$PatientType,SplitRatio = 0.7) > Train=subset(df,spl==TRUE) > Test=subset(df,spl==FALSE) > SecondTree=randomForest(PatientType~ cookie + curtains + get + mother + overflowing + sink +thats + window + stool + heres + drying + chair + okay +outside + standing + tipping + windows + blowing + breeze +counter + finger + onto + open + reaching + didnt + spilled +action + quiet + summer + mouth + puddle + good + wind +whos + sort,data = Train,nodesize=25,ntree=200,proximity=TRUE) > PredictForest=predict(SecondTree,newdata =Test)> Is MDS plot a way to find out if the classification are easy to be separated?This seems to be largely a statistics question and, if so, is OT here (this list is about R programming) I suggest you post this on stats.stackexchange.com instead. Cheers, Bert> > thanks for any help. > Elahe > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
Thanks for your reply Bert. But the question on how to plot MDS on predicted data I guess belong to here! On Thursday, May 25, 2017 9:43 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: Elahe: On Thu, May 25, 2017 at 8:15 AM, Elahe chalabi via R-help <r-help at r-project.org> wrote:> Hi all, > I have applied Random Forest on my data and divided data into test and rain set to see the prediction results and it seems good cause the accuracy is 82%. Now my question is how can I plot MDS on predicted data? here is my code: > > > > spl=sample.split(df$PatientType,SplitRatio = 0.7) > Train=subset(df,spl==TRUE) > Test=subset(df,spl==FALSE) > SecondTree=randomForest(PatientType~ cookie + curtains + get + mother + overflowing + sink +thats + window + stool + heres + drying + chair + okay +outside + standing + tipping + windows + blowing + breeze +counter + finger + onto + open + reaching + didnt + spilled +action + quiet + summer + mouth + puddle + good + wind +whos + sort,data = Train,nodesize=25,ntree=200,proximity=TRUE) > PredictForest=predict(SecondTree,newdata =Test)> Is MDS plot a way to find out if the classification are easy to be separated?This seems to be largely a statistics question and, if so, is OT here (this list is about R programming) I suggest you post this on stats.stackexchange.com instead. Cheers, Bert> > thanks for any help. > Elahe > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.