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The likelihood can be divided by a normalization term without affecting the classification to obtain.
We define the global MCI of a module as the sum of divergences across all species (extant or ancestral, except the LCA) divided by a normalization term, Z, defined as follows: ∑ s, t ∈ S, s ≠ t N s t, where S is the set of all species other than the LCA, t is s's immediate parent, and N st is the number of genes for which we have a module assignment in both s and t.
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The S source term from Eq. (7) was given by where S0 is a normalization term and σ s is the standard deviation.
Here the denominator measures the likelihood that signal is generated by model and signal is generated by model, whereas the numerator acts as a normalization term which takes into account the complexity of both signals.
The first is a normalization term for the folder's cosine similarity value, and the second penalizes a folder for each query term that is not matched by the folder.
The direct inputs are each multiplied by their respective normalization terms, following the form of Eq. 1.
As different neurons show different amounts of normalization, a normalization scaling term α is added to the equation.
This does not completely remove the normalization term for this stimulus, because the normalization has a non-zero baseline level of activity (Eq. 4).
To this end, this paper proposes a statistical approach to long-term solar energy availability characterization based on analysis of historical insolation data, augmented by a normalization procedure implementing straightforward data set transformations.
The atmospheric features are separated from the solar and instrumental features by a normalization procedure.
This was accompanied by a normalization of glucose uptake.
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