This isn’t the case for ML, especially Neural Nets

[rabhasan018542]

This was expected, because the new model was directed at this particular goal, while the current Page Authority merely attempted to predict whether one page would rank over another. Second, we found that the new model predicted whether one page would rank over another better than the previous Page Authority. This was especially pleasing, as it laid to rest many of our concerns that the new model would underperform on old quality controls due to the new training model.


How much better is the new model at predicting SERPs than the current PA? At gambling data brazil every interval — all the way down to position 4 vs 5 — the new model tied or out-performs the current model. It never lost. Everything was looking great. We then started analyzing outliers. I like to call this the “does anything look stupid?” test. Machine learning makes mistakes, just as humans can, but humans tend to make mistakes in a very particular manner. When a human makes a mistake, we often understand exactly why the mistake was made.


; we pulled URLs with high Page Authorities under the new model that happened to have zero organic traffic, and included them in the training set to learn for those errors. We quickly saw bizarre 90+ PAs drop down to much more reasonable 60s and 70s… another win. We were down to one last test. The problem with branded search Some of the most popular keywords on the web are navigational. People search Google for Facebook, Youtube, and even Google itself.