Error in RStudio while running decision tree (mac)
I am running a CART decision tree on a training set which I've tokenized using quanteda for a routine text analysis task. The resulting DFM from tokenizing was turned into a dataframe and appended with the class attribute I am predicting for.
Like many DFMs, the table is very wide (33k columns), but only contains about 5,500 rows of documents. Calling rpart on my training set returns a stack overflow error.
If it matters, to help increase the speed of calculations, I am using the doSNOW library so I can run the model on 3 out of 4 of my cores in parallel.
I've looked at this answer but can't figure out how to do the equivalent on my mac workstation to see if the same solution would work for me. There is a chance that even if I increase the ppsize of RStudio, I may still run into this error.
So my question is how do I increase the maxppsize of RStudio on a mac, or more generally, how can I fix this stack overflow so I can run my model?
Thanks!
r rstudio
edited Nov 20 '18 at 23:35
Dave
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
add a comment |
I am running a CART decision tree on a training set which I've tokenized using quanteda for a routine text analysis task. The resulting DFM from tokenizing was turned into a dataframe and appended with the class attribute I am predicting for.
Like many DFMs, the table is very wide (33k columns), but only contains about 5,500 rows of documents. Calling rpart on my training set returns a stack overflow error.
If it matters, to help increase the speed of calculations, I am using the doSNOW library so I can run the model on 3 out of 4 of my cores in parallel.
I've looked at this answer but can't figure out how to do the equivalent on my mac workstation to see if the same solution would work for me. There is a chance that even if I increase the ppsize of RStudio, I may still run into this error.
So my question is how do I increase the maxppsize of RStudio on a mac, or more generally, how can I fix this stack overflow so I can run my model?
Thanks!
r rstudio
edited Nov 20 '18 at 23:35
Dave
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
add a comment |
I am running a CART decision tree on a training set which I've tokenized using quanteda for a routine text analysis task. The resulting DFM from tokenizing was turned into a dataframe and appended with the class attribute I am predicting for.
Like many DFMs, the table is very wide (33k columns), but only contains about 5,500 rows of documents. Calling rpart on my training set returns a stack overflow error.
If it matters, to help increase the speed of calculations, I am using the doSNOW library so I can run the model on 3 out of 4 of my cores in parallel.
I've looked at this answer but can't figure out how to do the equivalent on my mac workstation to see if the same solution would work for me. There is a chance that even if I increase the ppsize of RStudio, I may still run into this error.
So my question is how do I increase the maxppsize of RStudio on a mac, or more generally, how can I fix this stack overflow so I can run my model?
Thanks!
r rstudio
edited Nov 20 '18 at 23:35
Dave
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
I am running a CART decision tree on a training set which I've tokenized using quanteda for a routine text analysis task. The resulting DFM from tokenizing was turned into a dataframe and appended with the class attribute I am predicting for.
Like many DFMs, the table is very wide (33k columns), but only contains about 5,500 rows of documents. Calling rpart on my training set returns a stack overflow error.
If it matters, to help increase the speed of calculations, I am using the doSNOW library so I can run the model on 3 out of 4 of my cores in parallel.
I've looked at this answer but can't figure out how to do the equivalent on my mac workstation to see if the same solution would work for me. There is a chance that even if I increase the ppsize of RStudio, I may still run into this error.
So my question is how do I increase the maxppsize of RStudio on a mac, or more generally, how can I fix this stack overflow so I can run my model?
Thanks!
r rstudio
r rstudio
edited Nov 20 '18 at 23:35
Dave
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
edited Nov 20 '18 at 23:35
Dave
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
edited Nov 20 '18 at 23:35
Dave
2,55971725
edited Nov 20 '18 at 23:35
Dave
2,55971725
edited Nov 20 '18 at 23:35
Dave
2,55971725
2,55971725
asked Nov 20 '18 at 16:59
user10463769user10463769
144
asked Nov 20 '18 at 16:59
user10463769user10463769
144
asked Nov 20 '18 at 16:59
user10463769user10463769
144
144
add a comment |
add a comment |
1 Answer
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In the end, I found that macs don't have this same command line option since the mac version of RStudio uses all available memory by default.
So the way I fixed this is by decreasing the complexity of the task by reducing the sparsity. I cleaned the document-term matrix by removing all tokens that did not occur in at least 5% of the corpus. This was enough to take a matrix with 33k columns down to a much more manageable 3k columns while still leading to a highly representative DFM.
answered Dec 2 '18 at 7:30
user10463769user10463769
144
add a comment |
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In the end, I found that macs don't have this same command line option since the mac version of RStudio uses all available memory by default.
So the way I fixed this is by decreasing the complexity of the task by reducing the sparsity. I cleaned the document-term matrix by removing all tokens that did not occur in at least 5% of the corpus. This was enough to take a matrix with 33k columns down to a much more manageable 3k columns while still leading to a highly representative DFM.
answered Dec 2 '18 at 7:30
user10463769user10463769
144
add a comment |
In the end, I found that macs don't have this same command line option since the mac version of RStudio uses all available memory by default.
So the way I fixed this is by decreasing the complexity of the task by reducing the sparsity. I cleaned the document-term matrix by removing all tokens that did not occur in at least 5% of the corpus. This was enough to take a matrix with 33k columns down to a much more manageable 3k columns while still leading to a highly representative DFM.
answered Dec 2 '18 at 7:30
user10463769user10463769
144
add a comment |
In the end, I found that macs don't have this same command line option since the mac version of RStudio uses all available memory by default.
So the way I fixed this is by decreasing the complexity of the task by reducing the sparsity. I cleaned the document-term matrix by removing all tokens that did not occur in at least 5% of the corpus. This was enough to take a matrix with 33k columns down to a much more manageable 3k columns while still leading to a highly representative DFM.
answered Dec 2 '18 at 7:30
user10463769user10463769
144
In the end, I found that macs don't have this same command line option since the mac version of RStudio uses all available memory by default.
So the way I fixed this is by decreasing the complexity of the task by reducing the sparsity. I cleaned the document-term matrix by removing all tokens that did not occur in at least 5% of the corpus. This was enough to take a matrix with 33k columns down to a much more manageable 3k columns while still leading to a highly representative DFM.
answered Dec 2 '18 at 7:30
user10463769user10463769
144
answered Dec 2 '18 at 7:30
user10463769user10463769
144
answered Dec 2 '18 at 7:30
user10463769user10463769
144
answered Dec 2 '18 at 7:30
user10463769user10463769
144
144
add a comment |
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