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Based on the predictor output, it is decided whether the channel is accessed or not.
Hence, collision rate is calculated for the predictor output when channel access is allowed.
Furthermore, it can also be deduced that once the NN is trained for prediction with appropriate data sets, the error between the desired and actual predictor output is significantly reduced.
The variance of the zero-mean white noise process V(f n ) is the minimum mean-square of the predictor output, which is given by: {sigma}_v^2=R 0 -{displaystyle sum_{sigma}_v^2=R 0 -{displaystyle
There is a negligible error between the targeted output and the predictor output, i.e., about 0.07, among the training of 100 data points or 800 slot(s) as shown in Figure 9.
The 29 features were first tested separately as single predictors and their effect on the prediction assessed with the t-value associated with the linear predictor output.
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A weighted predictor sum (Consensus) required linear transformation of predictor outputs as determined by factors analysis.
The XT predictors output provides predictions up to 14 amino acids from their respective ends.
A consensus method was then developed to consolidate the predictors' output and to correlate this with experimental mRNA expression data.
Per-residue predictors (such as the PONDR® group of predictors) output a score for each residue in a protein and are especially useful when applied to proteins having both structured and disordered regions.
The latter serves as the predictor-specific weight variables w predictor in the proposed weighted-scoring scheme (see Eqs. 1– 2) which combines the four predictors' outputs into a singular value normscore weighted.
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