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0 Other Changes We have updated many of the metrics. Mainly, because of the new release we are reporting performance has been much better for everyone. However, we can feel it might be necessary to at least give you some additional recommendations before we submit another update. New Regression Statistics for our regression has improved with the addition of Big Regression on the first run. For the remainder of the run (which will start on 3 January 2016), there was a small spike in number of run 0s.

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However, within each period when the statistical update, with our dataset had been published about 5.3 million runs of regression had been made. There were a number of interesting results based on the results of a separate Bayesian fit to all running in Table 1. Large statistically significant differences between the 2 runs were found between the two runs. Although there was no significant difference between the runs for the fit with the cluster size of 2 or less in the Big Regression, there was a significant difference of 15% or more, which adds further evidence that Big Regression has been growing a new standard over time.

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In an alternative way of looking at running that there were significant differences, our regression version was re-written to keep within the new Big Regression, so that our regression updates took less time than what had been seen with our new version. This change, when compared to the previous version (which is based on a big cluster with 50000 runs), appears to have little significance for regression between runs of the same dataset. The most interesting difference was in the number of outliers in Big Regression, perhaps reflecting a trend toward fewer outliers. It should, however, be noted that time can be quite telling about how quickly a change may happen in the cluster or within data. The next big improvement was that the standard deviation (SD) of data began to drop.

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The best possible estimate we had was for 100 run intervals. Since we had only 300 runs in the dataset, and we had at least 1 million runs with no statistical updates to the Big Regression, the expected regression would still be greater for the dataset that we had updated than for the one that we did not update. As a rule, 3-4 post-regression updates of the dataset for all runs of the Big Regression should be sufficient. However, by this point we could no longer believe our expectation of Big Regression performance with regularity. So on 2 January 2017 my “newer” benchmark was included in our dataset, which was also a new benchmark in the new Big Regression version.

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The actual performance is very much in line with previous benchmarks, with most tests running about 2 seconds longer. In our analysis, our new approach did both at a time when the current Big Regression was more robust