Applying a 50% threshold to the posterior probabilities allows us to recreate the predictions contained in lda.pred$class.

> sum(lda.pred$posterior[, 1] >= .5)
[1] 70
> sum(lda.pred$posterior[, 1] < .5)
[1] 182

Notice that the posterior probability output by the model corresponds to the probability that the market will decrease:

lda.pred$posterior[1:20, 1]
lda.class[1:20]

If we wanted to use a posterior probability threshold other than 50% in order to make predictions, then we could easily do so. For instance, suppose that we wish to predict a market decrease only if we are very certain that the market will indeed decrease on that day—say, if the posterior probability is at least 90%.

> sum(lda.pred$posterior[, 1] > .9)
[1] 0

No days in 2005 meet that threshold! In fact, the greatest posterior probability of decrease in all of 2005 was 52.02%.