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Figure 8 summarizes the six issues mentioned that are part of the ranking function developed.
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Most of the ranking methods use integration which needs more computations for fuzzy numbers with nonlinear membership functions.
The rank orders of GO terms were used to determine the top ranking functions of these genes.
The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory.
Ranking functions discovered by GP have been found to be significantly better than many of the other existing ranking functions.
Streaming audio services such as Spotify and Rdio have been part of the rankings since late last year.
To solve this problem, we propose using query-level loss functions in learning of ranking functions.
Based on the effect of the ranking results on the Radial Basis Function (RBF) classification, a weighted voting scheme is then introduced to re-rank features.
Allows the use of Kernels for learning ranking functions.
The same is true of any two regular ranking functions and Spohn conditionalization.
The experimental evaluation of the ranking function is described in Section "Choosing the ranking function coefficients".
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