title: library(clValid) - The number of items to be clustered is larger than 'maxitems'
body: <p>Whenever I call:</p>
  
  <pre><code>library(clValid)
  clValid(da_mat, nClust = 2:6,clMethods = "kmeans",method = "ward", validation = "internal",verbose = F,metric = "euclidean")
  </code></pre>
  
  <p>the following question appears:</p>
  
  <blockquote>
    <p>The number of items to be clustered is larger than 'maxitems'</p>
    
    <p>The memory and time required may be excessive, do you wish to continue?
    (y to continue, any other character to exit) </p>
  </blockquote>
  
  <p>and needs my reply. </p>
  
  <p>Since I am planning to run batch jobs instead of interactive, is there a way to reply "y" by default and overcome the issue?</p>
  
  <hr>
  
  <p>Data used (da_mat):     </p>
  
  <pre><code>    structure(c(14.7868119777342, 18.581126120385, 14.9380542011058, 
      14.5077833814058, 18.6887270063248, 13.0741953872578, 53.2213486367502, 
      39.2760892563872, 36.3286469516398, 52.3246464294083, 38.990008979225, 
      42.7636927315109, 0.0819287561682333, 50.6671528767015, 27.088911851741, 
      11.6300757205617, 3.7416468290551, 0.130577870633152, 10.7111700513842, 
      7.92007921157524, 4.20239387147403, 18.6006133123143, 3.41976482109355, 
      9.83152367073265, 8.3847667237175, 0.189099037138927, 26.6938467233072, 
      31.9060795220325, 6.12105122188164, 0.0180650936064567, 5.2157370804847, 
      124.043533670242, 14.1332279747881, 9.38900135957734, 13.3926195625374, 
      4.27618424370432, 0.0375176829667512, 33.1446378315951, 0.0614049643335593, 
      4.53544258526804, 8.12804295873311, 25.3345674781844, 10.0375758054181, 
      21.3057513221092, 9.72597841564975, 37.7604818528206, 12.9287407274725, 
      30.0144136692908, 23.0035643919209, 23.9552607614791, 15.5519230953427, 
      16.1852465091283, 17.2936372721978, 14.1822434590294, 17.4453505890696, 
      17.6242719274598, 7.80773010200648, 6.98066512271067, 7.35845771951367, 
      6.11094328808852, 6.46916086780156, 10.0194349375673, 54.136690647482, 
      7.52160138742296, 24.451969427976, 8.4140553010681, 15.3767677072593, 
      0, 10.829055163392, 20.3472035475676, 10.9096412376604, 19.7634185198672, 
      64.6796758310227, 20.5881970936764, 22.518256989877, 12.4840880160029, 
      29.4441314452399, 4.13536851306181, 29.872098381653, 10.0267827251423, 
      39.0586971508497, 13.9895229126691, 27.9057110547023, 42.542644983762, 
      36.591915833143, 49.1566010449703, 0, 8.74024166511789, 0, 47.3636486820286, 
      36.730704895388, 25.6158675380266, 19.6441325515105, 36.4635550034461, 
      46.7742288763349, 2.10449659580434, 26.8333031049105, 4.09585486512544, 
      4.25406069627922, 13.8121251188155, 3.52, 10.4, 3.02, 3.41, 3.06, 
      7.95, 3.74, 3.43, 8.49, 3.99, 4.2, 1.28, 4.51, 0.91, 3.14, 4.75, 
      4.83, 3.41, 2.79, 9.89, 8.66, 6.29, 24.04, 14.29, 5.85, 2.18, 
      1.77, 2.24, 9.06, 1.63, 26.81, 1.59, 14.53, 8.31, 12.83, 67.2, 
      8.67, 14.11, 4.55, 43.49, 10.31, 25.58, 7.66, 11.48, 5.57, 2.25, 
      3.01, 0.77, 14.17, 2.05, 56.3, 67.42, 74.9, 73.42, 83.65, 63.47, 
      70.08, 55.7, 53.51, 84.49, 54.48, 95.8, 77.05, 97.4, 85.83, 81.33, 
      81.93, 93.53, 90.15, 83.5, 82.25, 68.81, 24, 76.03, 86.69, 87.98, 
      91.5, 49.08, 76.81, 92.05, 13.22, 95.47, 60.54, 77.84, 63.85, 
      1.8, 80.17, 80.55, 89.16, 3.49, 8.61, 55.93, 84.72, 66.11, 84.3, 
      87.33, 72.54, 94.72, 72.69, 93.38, 34.74, 13.54, 18.44, 18.52, 
      9.96, 23.5, 21.5, 38.31, 35.39, 7.44, 38.04, 0.83, 8.89, 0.4, 
      5.63, 4.28, 3.28, 0.87, 2.8, 1.78, 5.39, 4.55, 40.4, 4.97, 0.91, 
      6.06, 0.85, 46.93, 5.75, 2.4, 52.96, 1.04, 6.13, 2.94, 4.57, 
      29.2, 4.09, 1.88, 3.29, 38.83, 75.35, 9.32, 2.23, 5.09, 1.44, 
      5.71, 4.42, 2.33, 9.09, 0.77, 2.53, 3.83, 1.78, 2.48, 1.82, 3.01, 
      1.99, 0.76, 0.18, 1.55, 1.59, 0.4, 7.73, 0.38, 2.7, 7.81, 8.28, 
      0.72, 2.16, 3.71, 1.88, 16.05, 9.48, 2.1, 5.72, 1.26, 4.32, 0.54, 
      6.48, 2.55, 3.97, 0.36, 15.21, 8.58, 15.96, 0.56, 4.64, 1.43, 
      1.8, 11.53, 2.75, 6.74, 3.76, 14.75, 6.68, 0.79, 17.63, 0.72, 
      0.85, 0.75), .Dim = c(50L, 6L), .Dimnames = list(NULL, c("souksou", 
      "mouksou", "kai", 
      "ta", "resta", "mou")))
  </code></pre>