The phrase "algorithm factors" is correct and usable in written English.
It can be used when discussing the various elements or components that influence or contribute to the functioning of an algorithm.
Example: "When analyzing the performance of the machine learning model, we must consider the algorithm factors that affect its accuracy."
Alternatives: "algorithm components" or "algorithm elements".
The algorithm factors in variables besides bike lanes, like confusing intersections, steep hills or busy streets, before spitting out the "best" route.
He highlights "Microsoft's approach to app charting" — the listings of Top Free, Top Paid, and so on — as one of the main ways that the company has taken the lead, with algorithm factors being more nuanced with Windows Phone.
Interestingly, the social popularity algorithm factors in things like the number of incoming links to a user's Labels.io profile, number of Google links to their "external links" (assuming that the more people link to a user's portfolio/project/blog, the better their reputation in their respective industry).
An algorithm experiment deals with a set of dependent variables called performance measures that are affected by a set of independent variables called factors; there are the problem factors, the algorithm factors, and the test environment factors.
Algorithm factors, specially for EAs, include multiple parameters related to its strategy to solve the problem, such as type of selection, mutation, and crossover, and in the case of PEAs, parameters related to parallel strategies, such as migration parameters.
As obvious in the figure, deviation reduction in this algorithm is when its parameters are set as follows: the number of initial particles on level 1, the number of repetitions on level 2, the maximum velocity of particles on level 1, and the inertia weight on level 3. Open image in new window Fig. 3 Chart of S/N rate of objective functions at different levels of MOPSO algorithm factors.
Scheduling is done by an algorithm factoring in data from Singu and third parties, including location and weather.
Changing the level of each individual factor systematically and then analyzing the main and interactive effects of the design factors by using the analysis of variance (ANOVA) leads to the optimal heuristic algorithm factor levels with regard to experimental cost.
Open image in new window Fig. 2 Plot of ( overline {text{RPI}} ) for the type of algorithm factor.
His primary methodological interests include Bayesian methods, spatial statistics, MCMC algorithms, factor analysis, latent variable models, and causal inference.
Factors significant at 0.10 in the bivariate analyses were entered into a stepwise algorithm, retaining factors in the model that were significant at the 0.05 level.
