Neural Network Toolbox™

Process matrices by removing rows with specified indices

Syntax

• [y,ps] = removerows(x,ind)
  [y,ps] = removerows(x,fp)
  y = removerows('apply',x,ps)
  x = removerows('reverse',y,ps)
  dx_dy = removerows('dx',x,y,ps)
  dx_dy = removerows('dx',x,[],ps)
  name = removerows('name');
  fp = removerows('pdefaults');
  names = removerows('pnames');
  removerows('pcheck',fp);
  

Description

removerows processes matrices by removing rows with the specified indices.

removerows(X,ind) takes X and an optional parameter,

X	N x Q matrix or a 1 x TS row cell array of N x Q matrices
ind	Vector of row indices to remove (default is [])

and returns

Y	Each M x Q matrix, where M == N-length(ind) (optional)
PS	Process settings that allow consistent processing of values

removerows(X,FP) takes parameters as a struct: FP.ind.

removerows('apply',X,PS) returns Y, given X and settings PS.

removerows('reverse',Y,PS) returns X, given Y and settings PS.

removerows('dx',X,Y,PS) returns the M x N x Q derivative of Y with respect to X.

removerows('dx',X,[],PS) returns the derivative, less efficiently.

removerows('name') returns the name of this process method.

removerows('pdefaults') returns the default process parameter structure.

removerows('pdesc') returns the process parameter descriptions.

removerows('pcheck',FP) throws an error if any parameter is illegal.

Examples

Here is how to format a matrix so that rows 2 and 4 are removed:

• x1 = [1 2 4; 1 1 1; 3 2 2; 0 0 0]
  [y1,ps] = removerows(x1,[2 4])
  

Next, apply the same processing settings to new values.

• x2 = [5 2 3; 1 1 1; 6 7 3; 0 0 0]
  y2 = removerows('apply',x2,ps)
  

Reverse the processing of y1 to get x1 again.

• x1_again = removerows('reverse',y1,ps)
  

Algorithm

In the reverse calculation, the unknown values of replaced rows are represented with NaN values.

See Also

fixunknowns, mapminmax, mapstd, processpca

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