(DataPoint dataPoint, int targetClass)
| 322 | } |
| 323 | |
| 324 | @Override |
| 325 | public void update(DataPoint dataPoint, int targetClass) |
| 326 | { |
| 327 | final Vec x_t = dataPoint.getNumericalValues(); |
| 328 | final double y_t = targetClass*2-1; |
| 329 | double score = x_t.dot(w); |
| 330 | |
| 331 | double v_t = 0; |
| 332 | if (diagonalOnly) |
| 333 | { |
| 334 | //Faster to set only the needed final values |
| 335 | for (IndexValue iv : x_t) |
| 336 | { |
| 337 | double x_t_i = iv.getValue(); |
| 338 | v_t += x_t_i * x_t_i * sigmaV.get(iv.getIndex()); |
| 339 | } |
| 340 | |
| 341 | } |
| 342 | else |
| 343 | { |
| 344 | sigmaM.multiply(x_t, 1, Sigma_xt); |
| 345 | v_t = x_t.dot(Sigma_xt); |
| 346 | } |
| 347 | |
| 348 | //Check for numerical issues |
| 349 | |
| 350 | if(v_t <= 0)//semi positive definit, should not happen |
| 351 | throw new FailedToFitException("Numerical issues occured"); |
| 352 | |
| 353 | double m_t = y_t*score; |
| 354 | |
| 355 | final double loss = max(0, phi*sqrt(v_t)-m_t); |
| 356 | |
| 357 | if(loss <= 1e-15) |
| 358 | { |
| 359 | if(!diagonalOnly) |
| 360 | zeroOutSigmaXt(x_t); |
| 361 | return; |
| 362 | } |
| 363 | final double alpha_t; |
| 364 | |
| 365 | |
| 366 | if(mode == Mode.SCWI || mode == Mode.CW) |
| 367 | { |
| 368 | double tmp = max(0, (-m_t*psi+sqrt(m_t*m_t*phiSqrd*phiSqrd/4+v_t*phiSqrd*zeta))/(v_t*zeta) ); |
| 369 | if(mode == Mode.SCWI) |
| 370 | alpha_t = min(C, tmp); |
| 371 | else |
| 372 | alpha_t = tmp; |
| 373 | |
| 374 | } |
| 375 | else//SCWII |
| 376 | { |
| 377 | final double n_t = v_t+1/(2*C); |
| 378 | final double gamma = phi*sqrt(phiSqrd*v_t*v_t*m_t*m_t+4*n_t*v_t*(n_t+v_t*phiSqrd)); |
| 379 | alpha_t = max(0, (-(2*m_t*n_t+phiSqrd*m_t*v_t)+gamma)/(2*(n_t*n_t+n_t*v_t*phiSqrd))); |
| 380 | } |
| 381 |
nothing calls this directly
no test coverage detected