Comments (3)
hello, thanks for sending the bug report
i don't have a mac machine currently to test this and will take me till the end
of
the week to get a hold of one.
it will be great if you can post what arguments you were passing, so i can
setup a
dummy test.
like, argument1: size NxD and type, you can get that via whos('argument1')
You can also put in a debug point at line 353 or classRF_Train.m and see if all
of
these variables are defined at that point.
X',int32(Y_new),length(unique(Y)),ntree,mtry,int32(ncat),
int32(maxcat), int32(sampsize), strata, Options, int32(ipi),
classwt, cutoff, int32(nodesize),int32(nsum), int32(n_size), int32(p_size),
int32(nsample)
if either one of them is non-existent, it will explain the error message.
I can suggest you compile and run the mex from the source rather than using the
precompiled mex if you need results in the next few days.
Original comment by abhirana
on 16 Feb 2010 at 2:11
from randomforest-matlab.
I'm having the same problem; RF classification on the Mac does not work. All
variables exist and are defined when passed into mexClassRF_train() but I still
get the error:
Too less/many parameters: You supplied 15??? One or more output arguments not
assigned during call to "mexClassRF_train".
Error in ==> classRF_train at 347
[nrnodes,ntree,xbestsplit,classwt,cutoff,treemap,nodestatus,nodeclass,bestvar,ndbigtree,mtry ...
Original comment by [email protected]
on 3 Oct 2011 at 5:03
from randomforest-matlab.
i am so sorry. i could never get access to a mac machine to compile the binary
so uploaded a user-supplied binary.
these instructions may help you compile directly from the source
http://code.google.com/p/randomforest-matlab/issues/detail?id=8
Original comment by abhirana
on 6 Oct 2011 at 12:55
from randomforest-matlab.
Related Issues (20)
- weak learner HOT 1
- Compiling on Mac Lion HOT 6
- Compiled mexmaci64 for OSX 10.8.2 (Mountain Lion) HOT 2
- about the unbalanced data HOT 32
- Segmentation violation problem HOT 2
- Hierarchical sampling of data? HOT 3
- memory leak in HOT 1
- probability of classes for highly skewed dataset HOT 2
- Feature Normalization HOT 1
- sampsize problem
- score values from random forest HOT 1
- MATLAB crashes after tens of thousands runs !! HOT 3
- Compilation Problems with Matlab 2014a on Mac HOT 7
- How to get individual tree predictions for regression HOT 2
- use library (gcc) in matlab and error with compile of mex HOT 1
- NaN data HOT 4
- multivariate label output in regression analysis
- Matlab (randomly) crash after a number of runs HOT 5
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from randomforest-matlab.