Comparison of values and classification

I have a excel spreadsheet with 14 Columns and 1084 rows. I have to comapre the data in each row to eachother. Would it also be possible to do any of these and if so how would i do it.

Mdl = fitcdiscr(Tbl,ResponseVarName)

Mdl = fitcnb(Tbl,ResponseVarName)

Mdl = fitcknn(Tbl,ResponseVarName)

Mdl = fitctree(Tbl,ResponseVarName)

Im not sure how to go about doing this and i am very lost so any help is appreciated.

Answer 1

[Kevin Holly]

Generate table:

matrix = rand(1084,4); % making 4 columns because I don't feel like creating 14 column names
Tbl = array2table(matrix);
Tbl.Properties.VariableNames = {'Example','VariableName','Thisone','Anotherone'}

Tbl = 1084×4 table
     Example     VariableName    Thisone     Anotherone
    _________    ____________    ________    __________

     0.008419       0.94549       0.57949      0.26174 
      0.88127       0.91574       0.85093      0.41558 
      0.90647       0.93937       0.96487    0.0085924 
      0.70741       0.35517       0.64649      0.10701 
     0.046089       0.79723        0.0688      0.26858 
      0.51422       0.28245       0.37771      0.72541 
      0.35115      0.094531       0.59553        0.311 
      0.39849       0.97084      0.027262     0.047593 
      0.97249       0.91244       0.48412      0.98297 
       0.4826       0.76309       0.94302      0.78793 
      0.79139       0.76139        0.3027      0.19743 
       0.6975         0.275        0.4691      0.57933 
      0.47841       0.33515       0.53218      0.72264 
    0.0011759       0.85494       0.30534      0.28503 
     0.085123       0.96305       0.44785      0.17248 
      0.56161       0.88413       0.91003     0.042377 

Note, you could just read your table from the Excel spreadsheet directly using readtable function.

Chose Response Variable

ResponseVarName = 'Thisone';

Mdl = fitcknn(Tbl,ResponseVarName)

Mdl = 
  ClassificationKNN
           PredictorNames: {'Example'  'VariableName'  'Anotherone'}
             ResponseName: 'Thisone'
    CategoricalPredictors: []
               ClassNames: [7.0290e-04 7.2041e-04 0.0015 0.0022 0.0039 0.0059 0.0063 0.0067 0.0074 0.0106 0.0112 0.0114 0.0123 0.0130 0.0155 0.0157 0.0169 0.0177 0.0183 0.0210 0.0212 0.0214 … ]
           ScoreTransform: 'none'
          NumObservations: 1084
                 Distance: 'euclidean'
             NumNeighbors: 1


  Properties, Methods

[Alexander]

Im getting an error that says not enough input arguments