quadratic representation of the data a quadratic representation of extends the linear representation to include cross terms. for example, if we want to construct the matrix (the quadratic representation of ) including the first three tumor features of , we would write: where each represents a column of and indicates element-wise-multiplication. construct a quadratic least square representation that includes four tumor features in - the data in breast-cancer-train.dat - as a 2d numpy array, and store it in the variable a quad. you are given a list called subset labels that contains the names of the 4 columns of the matrix that you should use in this quadratic representation. the setup code provides the following variables: name type description breast-cancer-train.dat data file on server a .dat file containing breast cancer dataset labels list a list of all available column labels subset labels list a subset of the available column labels to compute the data matrix a your code snippet should define the following variable(s) and/or function(s): name type description a quad 2d numpy array the quadratic representation for the subset columns of the data as a 2d numpy array of type float.