Comment by zelphirkalt
13 hours ago
What do you mean by processing one row at a time?
I think one could parallelize processing rows, at the very least when classifying from learned model. Probably also during learning the model.
13 hours ago
What do you mean by processing one row at a time?
I think one could parallelize processing rows, at the very least when classifying from learned model. Probably also during learning the model.
Yes you can certainly do that.
What I had not articulated well is that linear classifiers have the opportunity to use matvecs that have a different level of L1 L2 cacheable goodness and non-branchy code. There using proper memory layout gives an outstanding win. The win for decision trees are less impressive in comparison, so you needn't be feeling bad about your code.