Problem with running R code in the application

Hi @jozeftomas_2020

You are not specifying the CRAN mirror to be used to download and install your package. A quick and dirty workaround would be to change your first line (this one):

install.packages ("ppclust")

Change that to:

install.packages ("ppclust", repos = "http://cran.us.r-project.org")

Or better:

if (!require(ppclust)) install.packages ("ppclust", repos = "http://cran.us.r-project.org")

Or even better, don't invoke package installations from your RapidMiner extension, do it from R directly, and/or configure your .Rprofile file.

Hope it works for you.

All the best,

Hello
Thank you
I did it, but it's an error again.
I am a beginner and I do not know how to solve the problem.
Sorry maybe you help again?

And he also made a mistake in drawing up the wordcluod

(In a suicide, I need a lot of wordcluod):smileysad:
Do you have a sample code to run a clustering in the Rhapsody with the R code?
Thanks if you send

I'm a beginner in R, so I can't help you much. However, if you do the same you did in the first place for installing ppclust, it will work:

install.packages ("factoextra", repos = "http://cran.us.r-project.org")

Let's see how it goes this time.

Thanks a lot


Now this error

"there is no package fclust".

Install the package.

I wrote this
install.packages ("factoextra", repos = "http://cran.us.r-project.org")
Open the same error

You should try testing your R code inside R first.  If you get errors there, then you definitely won't get it to run inside RapidMiner.

In all the errors you have shown above, you appear to be referencing packages that don't exist---have you checked those package names carefully?

Hello
Thankful
The r code runs correctly. But there is an error in the rapidshare
Could you check in Rapidminer?
Thanks a lot

@jozeftomas_2020 your going to have to check if RapidMiner can access those packages. 

Hello
How and by what steps can I do?
May you tell me?
Thankful

@jozeftomas_2020 R loads it's packages into folders on your computer. You should check if it's loading them into your user account where RM Studio can access. Then I would just take one Execute R operator and the type in "require(some library)" and run the process. If it doesn't break or complain, then RM Studio can access the library. Repeat till all  your libraries are able to load. If one fails, then you'll need to open up the R console and install it in the right directory where RM can find it. 

Hi Dear Professor @Thomas_Ott
In this case, I Novice and beginner.
Can you tell me what steps to take?
Sorry to ask
With respect

@jozeftomas_2020 in your R console, type the following:

<SPAN class="pln">.libPaths</SPAN><SPAN class="pun">()</SPAN>

 That will tell you where the packages are being stored. Check that directory (or directories) to make sure the libraries are installed there. Then check where RapidMIner is calling the Rscript.exe from (see your RM Studio preferences). It could be that Rscript.exe is calling from a different R library. 

Hello
Thank you very much for your help.
I gave this path

C:/Program Files/R/R-3.4.3/bin/Rscript.exe

I put this code in the script to draw the word cloud, but it did not work
If my RAM is high. And how many times I tried. But this error every time.
How to tell the code in the script on my data and on the third column of that text?

Can I help me again?
Thank you
With respect

library("tm")
library("SnowballC")
library("wordcloud")
library("RColorBrewer")

# Read the text file from internet
filePath <- "C:/pfull_1.csv"
text <- readLines(filePath)
docs <- Corpus(VectorSource(text))
inspect(docs)
toSpace <- content_transformer(function (x , pattern ) gsub(pattern, " ", x))
docs <- tm_map(docs, toSpace, "/")
docs <- tm_map(docs, toSpace, "@)
docs <- tm_map(docs, toSpace, "\\|")
# Convert the text to lower case
docs <- tm_map(docs, content_transformer(tolower))
# Remove numbers
docs <- tm_map(docs, removeNumbers)
# Remove english common stopwords
docs <- tm_map(docs, removeWords, stopwords("english"))
# Remove your own stop word
# specify your stopwords as a character vector
docs <- tm_map(docs, removeWords, c("blabla1", "blabla2"))
# Remove punctuations
docs <- tm_map(docs, removePunctuation)
# Eliminate extra white spaces
docs <- tm_map(docs, stripWhitespace)
# Text stemming
# docs <- tm_map(docs, stemDocument)
dtm <- TermDocumentMatrix(docs)
m <- as.matrix(dtm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v)
head(d, 10)
set.seed(1234)
wordcloud(words = d$word, freq = d$freq, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))

@jozeftomas_2020 i think you have to write out wordcloud image. right after 'set.seed(1234)' try adding

png("wordcloud.png", width=1280,height=800)
wordcloud(words = d$word, freq = d$freq, min.freq = 1,
 max.words=200, random.order=FALSE, rot.per=0.35, 
 colors=brewer.pal(8, "Dark2"))
dev.off()

 You might have to path wordcloud.png to some directory or it will save it to the default R directory somewhere.

Hello dear Professor @Thomas_Ott
I wrote this

png ("D: /wordcloud.png", width = 1280, height = 800)
wordcloud (words = d $ word, freq = d $ freq, min.freq = 1,
  max.words = 200, random.order = FALSE, rot.per = 0.35,
  colors = brewer.pal (8, "dark2"))
dev.off ()


But again the same error went up.
Please tell me what is the problem?
Is it possible to send me the process that was implemented?
Thank you very much for your help

And I'm going to run the code on my data
I loaded the data and then with the 'select attribute' operator I chose my text column and then I connected to the 'excute R' operator, but the same error occurred again.
Could you guide how to provide data and text columns to run the code?
Sorry sorry i'm asking

With respect

hello

sorry..

please help me..

:smileysad:

No matter how hard I try. It's not good. And I am not able to draw the words of the cloud

@jozeftomas_2020 Here you go. This is simplified using the Text Processing extension in RapidMiner. I just used a bit of R code to draw the word cloud.

<?xml version="1.0" encoding="UTF-8"?><process version="8.2.001">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="8.2.001" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="social_media:search_twitter" compatibility="8.1.000" expanded="true" height="68" name="Search Twitter" width="90" x="45" y="34">
        <parameter key="connection" value="Twitter"/>
        <parameter key="query" value="rapidminer"/>
      </operator>
      <operator activated="true" class="select_attributes" compatibility="8.2.001" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="34">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="Text"/>
      </operator>
      <operator activated="true" class="nominal_to_text" compatibility="8.2.001" expanded="true" height="82" name="Nominal to Text" width="90" x="313" y="34">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="Text"/>
      </operator>
      <operator activated="true" class="text:process_document_from_data" compatibility="8.1.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="447" y="34">
        <parameter key="prune_method" value="percentual"/>
        <list key="specify_weights"/>
        <process expanded="true">
          <operator activated="true" class="text:tokenize" compatibility="8.1.000" expanded="true" height="68" name="Tokenize" width="90" x="112" y="34"/>
          <connect from_port="document" to_op="Tokenize" to_port="document"/>
          <connect from_op="Tokenize" from_port="document" to_port="document 1"/>
          <portSpacing port="source_document" spacing="0"/>
          <portSpacing port="sink_document 1" spacing="0"/>
          <portSpacing port="sink_document 2" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="text:wordlist_to_data" compatibility="8.1.000" expanded="true" height="82" name="WordList to Data" width="90" x="581" y="85"/>
      <operator activated="true" class="select_attributes" compatibility="8.2.001" expanded="true" height="82" name="Select Attributes (2)" width="90" x="715" y="85">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attributes" value="word|total"/>
      </operator>
      <operator activated="true" class="r_scripting:execute_r" compatibility="8.1.000" expanded="true" height="82" name="Execute R" width="90" x="849" y="85">
        <parameter key="script" value="# rm_main is a mandatory function, &#10;# the number of arguments has to be the number of input ports (can be none)&#10;rm_main = function(data)&#10;{&#10;&#9;library(&quot;wordcloud&quot;)&#10;&#9;library(&quot;RColorBrewer&quot;)&#10;&#9;&#10;&#9;png(&quot;C:\\Users\\TomOtt\\Desktop\\wordcloud.png&quot;, width=1280,height=800)&#10;&#9;wordcloud(words = data$word, freq = data$total, min.freq = 1, max.words=200, random.order=FALSE, rot.per=0.35, colors=brewer.pal(8, &quot;Dark2&quot;))&#10;&#9;dev.off()&#10;&#9;&#10;&#9;return (data)&#10;}&#10;"/>
      </operator>
      <connect from_op="Search Twitter" from_port="output" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Select Attributes" from_port="example set output" to_op="Nominal to Text" to_port="example set input"/>
      <connect from_op="Nominal to Text" from_port="example set output" to_op="Process Documents from Data" to_port="example set"/>
      <connect from_op="Process Documents from Data" from_port="word list" to_op="WordList to Data" to_port="word list"/>
      <connect from_op="WordList to Data" from_port="example set" to_op="Select Attributes (2)" to_port="example set input"/>
      <connect from_op="Select Attributes (2)" from_port="example set output" to_op="Execute R" to_port="input 1"/>
      <connect from_op="Execute R" from_port="output 1" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>

@jozeftomas_2020 do a search through the community for a sample of clustering with text data, there in there somewhere. I can't help you right now because I'm swamped with work. Maybe some other intrepid community member can help!

Hello
Thomas_Ott
So much thanks so much.
Thank you
I ask other friends if it is possible for you. Help me out here?
How do you make steps like this?
(stemming, tokenize, filter token by length, remove stop word),
And then tf / idf and I can do hierarchical and clustering. Like RapidMiner 
  Do I do with R code? Of course, in the RapidMiner program.
Just enter the data and bring the execute R operator. Do all the preprocessing steps and tf / idf and clustering by R?
Thanks if you help
Thanks

There are operators for all of these standard text mining functions built directly into RapidMiner, which can be used inside the "Process Documents" operator.  That operator will also generate the TF-IDF word vector.  No need to use R for all that.  If you search the forum for text mining, you will find many existing threads with examples of these.