Sentence examples for normalize information from inspiring English sources

The original implementation of PELT in "changepoint" package [ 14] makes the penalty value dependent on the size of data to normalize information content.

Because the aquatic toxicity of AES varies according to alkyl and ethoxylate chain lengths, QSARs have been used to "normalize" information from diverse structures to a single structure or mixture which can then be used to compare the toxicity data and eventually derive the aquatic PNEC described by van de Plassche et al. (1999).

NGD is grounded in the well-established theory of Kolmogorov complexity [ 20] and the Normalized Information Distance (NID) between two objects [ 21].

This suggests that the integration of the extracted and normalized information from different databases into a unified and comprehensive resource is very necessary.

Another shortcoming of the present study is the lack of inclusion of a healthy control group undergoing the same stimulations, although this would not add anything to the results of the study because the healthy subjects usually already habituate normally at the baseline, i.e. we cannot normalize the already normal information processing.

In order to get comparable results for each region, we normalize the information presented in Table 5.

A wide variety of transformations and feature extraction steps has already been employed in Gaussian mixture model-hidden Markov model (GMM-HMM -based speech recoGMM-HMM -baseds to extract and normalize the information contained in the input speech siGMM-HMM -basedently aspeechible.

Thus, we considered it a necessity to create a common representation to normalize the information irrespective of the original wording of the sentences in a paper.

(NMI) Normalized Mutual Information score: is an normalization of the Mutual Information score that measure the mutual information between two clusterings.

By normalizing this information by the total number of occurrences of that echo pair, the posterior probability of each tissue class was generated (i.e., the probability of UTE echo pair (x, y) being obtained for air/bone/soft tissue).

In an effort to further remove this bias, we approximate the column normalized mutual information distributions as Gaussian distributions (Figure 1C).