RSEはLiとZhouによって提案されたアンサンブル枝刈りをQP問題へと帰着させる手法．
いい点
数式もTeX形式で簡単
$$ R(\boldsymbol{w}) = \lambda V(\boldsymbol{w}) + \Omega(\boldsymbol{w}) $$
R(\\boldsymbol{w}) = \\lambda V(\\boldsymbol{w}) + \\Omega(\\boldsymbol{w})
/**
* get the matrix W for Laplacian
* @return w_link filename
* @throws Exception
*/
public String[] getKernelLinkMatrix(byte[] data, String fold) throws Exception {
System.out.println("\\t\\t[*] Hello from Java!");
// get the link matrix
// create java matrix from numpy
Instances d = createFromPy4j(data);
Matrix LMat = new Matrix(m_numInst, m_numInst);
RBFKernel krl = new RBFKernel();
double g = 0.5 / m_numAttr;
krl.setGamma(g);
krl.buildKernel(d);
System.out.println("\\t\\t[*] calculating w_link on Java...");
for (int i = 0; i < m_numInst; i++) {
for (int j = 0; j <= i; j++) {
double vt = krl.eval(i, j, d.instance(i));
LMat.set(i, j, vt);
LMat.set(j, i, vt);
}
}
d = null;
krl = null;
System.out.println("\\t\\t[-] calc done...");
return returnFilename(LMat, m_numInst, fold);
}