title: running tune.svm in R and taking long time
body: <p>I have a data set for emails and I am using SVM to decide whether an email is a spam or not</p>
  
  <p>I divided the data set into test and training and then picked a random set of 500 records to tune the svm. I am using RBF kernel. Below is the raw data </p>
  
  <pre><code>make,address,all,num3d,our,over,remove,internet,order,mail,receive,will,people,report,addresses,free,business,email,you,credit,your,font,num000,money,hp,hpl,george,num650,lab,labs,telnet,num857,data,num415,num85,technology,num1999,parts,pm,direct,cs,meeting,original,project,re,edu,table,conference,charSemicolon,charRoundbracket,charSquarebracket,charExclamation,charDollar,charHash,capitalAve,capitalLong,capitalTotal,type
  0,0.64,0.64,0,0.32,0,0,0,0,0,0,0.64,0,0,0,0.32,0,1.29,1.93,0,0.96,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.778,0,0,3.756,61,278,spam
  0.21,0.28,0.5,0,0.14,0.28,0.21,0.07,0,0.94,0.21,0.79,0.65,0.21,0.14,0.14,0.07,0.28,3.47,0,1.59,0,0.43,0.43,0,0,0,0,0,0,0,0,0,0,0,0,0.07,0,0,0,0,0,0,0,0,0,0,0,0,0.132,0,0.372,0.18,0.048,5.114,101,1028,spam
  0.06,0,0.71,0,1.23,0.19,0.19,0.12,0.64,0.25,0.38,0.45,0.12,0,1.75,0.06,0.06,1.03,1.36,0.32,0.51,0,1.16,0.06,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,0,0,0.12,0,0.06,0.06,0,0,0.01,0.143,0,0.276,0.184,0.01,9.821,485,2259,spam
  0,0,0,0,0.63,0,0.31,0.63,0.31,0.63,0.31,0.31,0.31,0,0,0.31,0,0,3.18,0,0.31,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.137,0,0.137,0,0,3.537,40,191,spam
  0,0,0,0,0.63,0,0.31,0.63,0.31,0.63,0.31,0.31,0.31,0,0,0.31,0,0,3.18,0,0.31,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.135,0,0.135,0,0,3.537,40,191,spam
  
  
  svmFit = tune.svm(type~., data = randomTrainSample,
             gamma = 2^(0.000001:0.001), cost = 2^(10:100))
  </code></pre>
  
  <p>This process goes on for a very long time and does not seem to end.                             </p>
  
  <p>I also ran it with gamma = 2^(-1:1) and cost = 2^(2:4). It worked fine But with the above values it gives almost no results.</p>
  
  <p>I suspect it is due to the value of gamma and the cost that I am providing. Can anyone suggest?</p>