public double iterateUntilConvergence(double minFractionalErrorChange, int maxIterations, int minIter) { return iterateUntilConvergence(minFractionalErrorChange, maxIterations, minIter, 0); }
public double iterateUntilConvergence(double minFractionalErrorChange, int maxIterations, int minIter) { return iterateUntilConvergence(minFractionalErrorChange, maxIterations, minIter, 0); }
public double iterateUntilConvergence(double minFractionalErrorChange, int maxIterations, int minIter) { return iterateUntilConvergence(minFractionalErrorChange, maxIterations, minIter, 0); }
new InMemoryCollapsedVariationalBayes0(sampledCorpus, terms, numTestTopics, ALPHA, ETA, 2, 1, 0); cvb.setVerbose(true); perps[trial] = cvb.iterateUntilConvergence(0, 5, 0, 0.2); System.out.println(perps[trial]);
cvb0.iterateUntilConvergence(minFractionalErrorChange, maxIterations, burnInIterations); logTime("total training time", System.nanoTime() - start);
cvb0.iterateUntilConvergence(minFractionalErrorChange, maxIterations, burnInIterations); logTime("total training time", System.nanoTime() - start);
cvb0.iterateUntilConvergence(minFractionalErrorChange, maxIterations, burnInIterations); logTime("total training time", System.nanoTime() - start);