public void trainDocuments(double testFraction) {
long start = System.nanoTime();
modelTrainer.start();
for (int docId = 0; docId < corpusWeights.numRows(); docId++) {
if (testFraction == 0 || docId % (1 / testFraction) != 0) {
Vector docTopics =
new DenseVector(numTopics).assign(1.0 / numTopics); // docTopicCounts.getRow(docId)
modelTrainer.trainSync(corpusWeights.viewRow(docId), docTopics, true, 10);
}
}
modelTrainer.stop();
logTime("train documents", System.nanoTime() - start);
}
