The phrase "a best algorithm" is not correct in standard written English.
It is typically used incorrectly because "best" is a superlative adjective and should not be preceded by an article like "a."
Example: "After extensive testing, we determined the best algorithm for our needs."
Alternatives: "the optimal algorithm" or "the most effective algorithm."
Comparison of the three classification algorithms (NB, BN and NN) yielded a best algorithm in terms of classification accuracy.
Our intent with this analysis was not to identify a "best" algorithm for approximating heat index, but rather to determine whether algorithms used in the literature produce values that reasonably agree with the theoretical concepts underlying Steadman's original apparent temperature.
Note that the main contribution of this study is to propose a DE framework, and not to propose a "Best" algorithm or competitor to defeat other state-of-the-art algorithms.
Rather than search for a single best algorithm, researchers have sought to integrate a variety of methods in order to reap the benefits of methodological complementarity (Van Der Laan et al. 2007; Rokach 2009; Chandrasekaran and Jordan 2013).
Even the comparative study in [19] is not able to find a clear best algorithm.
Using the combinatorial fusion methods described here, there is no need to depend on a single "best" algorithm.
However, a closer inspection of Table 2 shows that it is difficult to select a single best algorithm among the group of top-performing algorithms.
The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R2 of 0.706.
We show how these properties can be used to drive, given a set of illuminant estimation algorithms, the selection of the best algorithm for a given image.
The classification formulation allowed us to pool more candidate peaks identified by different peak calling algorithms at relaxed cutoff thresholds so that we did not have to rely on a single "best" algorithms and "optimal" parameterization but resorted to our classification to identify functional ERα/SRC-1 DNA binding.
That is, for 10 additional counts, sensitivity was 49.8% for the initial algorithm and 85.3% for the best algorithm, an improvement of 35.5%.
