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The CFOP method (Cross – F2L (first 2 layers) – OLL (orientate last layer) – PLL (permutate last layer)), also known as the Fridrich method, is one of the most commonly used methods in speedsolving a 3×3×3 Rubik's Cube. It is one of the fastest methods with the other most notable ones being Roux and ZZ.
Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result, the formula can be used as a measure of the bias in the forecasts.
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
In 3×3×3 blindfolded and 3×3×3 fewest moves challenges, either a straight mean of 3 or the best of 3 is used, while 4×4×4 blindfolded, 5×5×5 blindfolded, and multiple blindfolded challenges are ranked using the best of 1, 2 or 3, depending on the competition. When a round begins, competitors turn in the puzzle they will use.
In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.
The following are the current official speedcubing world records approved by the WCA. [4] Note: For averages of 5 solves, the best time and the worst time are dropped, and the mean of the remaining 3 solves is taken. For events where only 3 solves are done, the mean of all 3 is taken.
Tay, Mareels and Moore (1998) defined settling time as "the time required for the response curve to reach and stay within a range of certain percentage (usually 5% or 2%) of the final value." [ 2 ] Mathematical detail
The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or of an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).