"optimized prediction" is a correct and usable phrase in written English.
You can use it when you are referring to a prediction that has been improved or made more accurate through the use of optimization techniques. For example, "The optimized prediction indicated that the stock market would experience a sharp fall."
The predicted secondary structure of the consensus DART domain, as predicted by the SOPMA (Self Optimized Prediction Method from Alignments) method [9] is for a helical structure (Figure 5).
This is because the quantities that can be shown to be (locally) optimized by some training algorithms do not necessarily translate into an optimized prediction accuracy as defined by us here.
In addition to developing a risk score that could be implemented in the near future, these results more broadly support the utility of super learning to develop optimized prediction functions for mental health outcomes.
It is a well-known fact that the P2AR optimization has a closed-form solution as follows: beta ={left({X}^TXright)}^{-1}left({X}^TYright) (5 where β = [β(1) β(2) ⋯ β(N)] T is the optimized prediction coefficients which have to be multiplied by the support pixels.
With the optimized prediction matrices, dereverberated signals can be obtained as prediction errors, that is, a dereverberated STFT coefficient vector can be computed as, begin{array}{*{20}l} boldsymbol{x}_{n} = boldsymbol{y}_{n} - sum_{tau = T_{bot}}^{T_{top}} boldsymbol{G}_{tau}^{H} boldsymbol{y}_{n - tau}.
The optimized prediction model with 263 features was also tested on an independent dataset, and the accuracy was still 80.00%.
If we are able to make an accurate noise distribution assumption for a particular regression problem, the proposed framework should give optimized predictions and error intervals and, in particular, surpass classical (epsilon -SVR accuracy.
We developed a set of automated procedures that systematically examined possible metabolic modifications to the original iNJ661 network and optimized predictions of experimental in vivo essentiality.
Self-optimized prediction method (SOPM) has been described to improve the success rate in the prediction of the secondary structure of proteins.
Aself-optimized prediction method with alignment or SOPMA is employed for calculation of the secondary structural features of triose phosphate isomerase.
We present an optimized predictive model (named symphony) that integrates predictions from in silico models.
