title: How to solve "rank-deficient fit may be misleading error" on my linear model?
body: <p>I have a problem when I use my model to do some prediction, R shows this message <code>Warning message prediction from a rank-deficient fit may be misleading</code>, how can I solve it? I think my model is correct is the prediction that fails and I don't know why.</p>
  
  <p>Here you can see step by step what I am doing and the summary of model:</p>
  
  <pre><code>myModel &lt;- lm(margin~.,data = dataClean[train,c(target,numeric,categoric)])
  
  Call:
  lm(formula = margin ~ ., data = dataClean[train, c(target, numeric, categoric)])
  
  Residuals:
    Min        1Q    Median        3Q       Max 
  -0.220407 -0.035272 -0.003415  0.028227  0.276727 
  
  Coefficients: (2 not defined because of singularities)
                                     Estimate Std. Error t value Pr(&gt;|t|)    
  (Intercept)                          6.061e-01  2.260e-02  26.817  &lt; 2e-16 ***
  price                                1.042e-05  8.970e-06   1.162 0.245610    
  shipping                             1.355e-03  2.741e-04   4.943 9.25e-07 ***
  categoryofficeSupplies              -7.721e-02  2.295e-02  -3.364 0.000802 ***
  categorytechnology                  -3.993e-02  2.325e-02  -1.717 0.086249 .  
  subCategorybindersAndAccessories    -1.650e-01  1.421e-02 -11.612  &lt; 2e-16 ***
  subCategorybookcases                 3.337e-04  2.328e-02   0.014 0.988565    
  subCategorychairsChairmats          -3.104e-02  2.106e-02  -1.474 0.140831    
  subCategorycomputerPeripherals       1.356e-02  1.293e-02   1.049 0.294604    
  subCategorycopiersAndFax            -1.943e-01  2.944e-02  -6.598 7.27e-11 ***
  subCategoryenvelopes                -1.648e-01  2.045e-02  -8.057 2.62e-15 ***
  subCategorylabels                   -1.534e-01  1.984e-02  -7.730 3.00e-14 ***
  subCategoryofficeFurnishings        -8.827e-02  2.220e-02  -3.976 7.61e-05 ***
  subCategoryofficeMachines           -1.521e-01  1.639e-02  -9.281  &lt; 2e-16 ***
  subCategorypaper                    -1.624e-01  1.363e-02 -11.909  &lt; 2e-16 ***
  subCategorypensArtSupplies          -8.484e-04  1.524e-02  -0.056 0.955623    
  subCategoryrubberBands               3.174e-02  2.245e-02   1.414 0.157854    
  subCategoryscissorsRulersTrimmers    1.092e-01  2.327e-02   4.693 3.13e-06 ***
  subCategorystorageOrganization       1.219e-01  1.575e-02   7.739 2.82e-14 ***
  subCategorytables                           NA         NA      NA       NA    
  subCategorytelephoneAndComunication         NA         NA      NA       NA    
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  
  Residual standard error: 0.08045 on 858 degrees of freedom
  Multiple R-squared:  0.6512,    Adjusted R-squared:  0.6439 
  F-statistic: 88.98 on 18 and 858 DF,  p-value: &lt; 2.2e-16
  
  estimateModel &lt;- predict(myModel, type="response", newdata=dataClean[test, c(numeric,categoric,target)])
  
  Warning message:
  In predict.lm(myModel, type = "response", newdata = dataClean[test,  :
  prediction from a rank-deficient fit may be misleading
  </code></pre>