Export the rows that makes the confusion matrix

[Rolf Edberg]

Hi

 

How can I export the rows that are used to form the confusion matrix?

 

I want to continue to make calculations on the rows that makes the result in the confusion matrix including TP, FP, TN and FN.

 

How can I export all the rows (incl the parameters) into an csv flie or Excel file?

 

Regards,

Rolf

 

 

[Graham Williams]

Have a look in the Log tab. The code to generate the matrix is included there.

For the weather dataset, I see the following code used to generate the matrix:

> table(crs$dataset[crs$validate, c(crs$input, crs$target)]$RainTomorrow, crs$pr, dnn=c("Actual", "Predicted"))

Wrap this in a write.csv to save a csv file:

> write.csv(table(crs$dataset[crs$validate, c(crs$input, crs$target)]$RainTomorrow, crs$pr, dnn=c("Actual", "Predicted")), file="tmp.csv")

Is that what you meant? 

Graham Williams

http://togaware.com

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[Graham Williams]

On 11 June 2013 18:16, <gerard...@gmail.com> wrote:

Hi,

 

Rattle is not responding (meaning nothing happens) when I execute Associate (including basket).

 

In R the following error is displayed:

 

Error in executeAssociateTab() : attempt to apply non-function

 

I think it is has to do with running Rattle on a Mac

 

Lion OS X 10.8.3

R version 2.15.3

Rattle 2.6.26

 

Does anyone have a solution?

 

Regards Gerard

I wonder if you have arules installed - Rattle should be picking that up so I don't think that is the actual problem. 

You could try the latest version of Rattle to see if that fixes the problem:

> install.packages("rattle", repos="http://rattle.togaware.com", type="source")

 

Hope that helps.

Graham Williams

http://togaware.com

[Rolf Edberg]

Hi Graham,

I get the following error if I try to create the csv-file:

Error in table(crs$dataset[crs$validate, c(crs$input, crs$target)]$RainTomorrow,  :

  all arguments must have the same length

 

My goal in the weather dataset would be to take the sum of RISK_MM from the 205 TP and compare it with the sum of the RISK_MM from the 27 FP. Sometimes the RISK_MM is smaller or bigger in the TP than the FP. (In the weather dataset is the TP no(Pre)/no(Act) and the FP(no(Pre)/yes(Act))

 

How do I do that?

 

Kind regards,

Rolf

[Bob Nisbet]

It is easier to just do it all in Excel.  Export the scored list, and create your own confusion matrix with Excel formulas.  I do it all the time with output from other data mining tools.

 

Bob Nisbet

[Rolf Edberg]

Thank you for the advise!!

 

What I am worried about is that the RISK_MM at the False Positive ( the wrong predictions) is worse than the average RISK_MM. That is the reason I want the RISK_MM that is the wrong predictions.

 

Rolf

[timeitself]

I have the same situation, with Mac OS 10.9.2 (Mavericks).

Everything else seems to work fine.

The Rattle version I have is 2.6.27 100.

I'm using Rattle in a Data mining course I'm teaching at the Stevens Institute of Technology and Basket Analysis is one of the topics ...

Carlo

[Graham Williams]

Did you give it a try with the latest version of rattle?

> install.packages("rattle", repos="http://rattle.togaware.com", type="source")

This should be fixed there.

Graham Williams

http://togaware.com

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[timeitself]

I updated it to the latest Rattle version (3.0.3), but still not working.

Also, I'm using R 2.15, because R 3 seems to be in conflict with the graphic libraries, mapping all the Rattle characters with squares.

Moving Rattle to a Ubuntu VM seems to be the most feasible work around.

Thanks

Carlo

[Stephen]

Hello,

I have the same problem, Mac OS X 10.9.2 (Mavericks), R version 3.0.3, Rattle 3.0.3. In the log, I have:

# Association Rules 

# The 'arules' package provides the 'arules' function.

require(arules, quietly=TRUE)

I also get these errors with clustering when clicking “Execute” (using the weather sample data):

Error in executeClusterKMeans(include) : attempt to apply non-function 

Error in executeClusterEwkm(include) : attempt to apply non-function

In the log, I have:

# KMeans 

# Reset the random number seed to obtain the same results each time.

set.seed(crv$seed)

and

# Entropy Weighted KMeans 

# The 'weightedKmeans' package provides the 'ewkm' function.

require(weightedKmeans, quietly=TRUE)

# Reset the random number seed to obtain the same results each time.

set.seed(crv$seed)

Stephen

[Graham Williams]

These issues are now fixed in Rattle version 3.0.4

> install.packages("rattle", repos="http://rattle.togaware.com", type="source")

Thanks for the assistance in resolving the issues.