Comments (9)
i am a bit confused by your issue.
so are the features individual examples? and you have test features for which
you want a label for?
votes for each example can be obtained from the predict function for both
classificaiton and regression
e.g.
http://code.google.com/p/randomforest-matlab/source/browse/trunk/RF_Class_C/tuto
rial_ClassRF.m#225
Original comment by abhirana
on 1 Feb 2012 at 7:29
from randomforest-matlab.
thank you for your reply.
actually, i am producing multiple feature based classifications of the same
subject, storing result in different variables.
now how to use random forest to voting for the best classification available?
where should i put my variables and how to use them??
i have seen the source code but could not use it further.
any help would be highly appreciated!
Original comment by [email protected]
on 1 Feb 2012 at 7:37
from randomforest-matlab.
i am still confused
so you have multiple examples per subject?
the simplest way is to take a look at the tutorial files and look at the
representation of the datasets (either twonorm or diabetes dataset are run in
those tutorial files)
assuming X is of size N x D where N is the number of examples and D is the
number of features/variables. and Y is of size N x 1.
then you can use classRF_train(X,Y) and it will return back the forest
structure, lets say model, which you can use with classRF_predict(X,model) to
get for a different X matrix
does that help?
Original comment by abhirana
on 1 Feb 2012 at 7:43
from randomforest-matlab.
u still do not get my question.
i am extracting features from my subject by different ways and each extracted
feature is stored in a variable. now i want to use random forest in such a way
so that it could take those feature variables as input, classify them based on
features and produce me output for best possible features.
now, how we can use random forest in this case?
hope i made my self clear this time.
Original comment by [email protected]
on 1 Feb 2012 at 7:51
from randomforest-matlab.
i think its a representation issue. all i can say is that random forests or
general purpose classifiers are useful if you can represent your data in a
matrix for inputs (what i am guessing is in the variable right now) and your
targets in a vector.
i dont know how you can use random forests if you cannot represent in a
matrix/vector form
Original comment by abhirana
on 1 Feb 2012 at 7:56
from randomforest-matlab.
the variables that i have are in matrix form.
what next?
Original comment by [email protected]
on 1 Feb 2012 at 9:10
from randomforest-matlab.
do take a look at the tutorial file
http://code.google.com/p/randomforest-matlab/source/browse/trunk/RF_Class_C/tuto
rial_ClassRF.m#38
model = classRF_train(X_trn,Y_trn); %to train
Y_hat = classRF_predict(X_tst,model); %to get the labels for X_tst
Original comment by abhirana
on 1 Feb 2012 at 9:24
from randomforest-matlab.
the input data in matrix form would be given as input to variable X_train, i
guess.what would be input to Y_train??
Original comment by [email protected]
on 7 Mar 2012 at 4:05
from randomforest-matlab.
Original comment by abhirana
on 31 Mar 2012 at 8:40
- Changed state: Done
from randomforest-matlab.
Related Issues (20)
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