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Sentiment analysis and opinion mining is out of its earlier stages and there is a strong need to standardize the datasets and evaluation methodology (Schouten and Frasincar 2015).
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For better comparability between the strains, we subsequently standardized the datasets such that the Tc importin α1 levels are identical in both strains (see Materials and Methods).
In spite of aspect extraction and sentiment analysis based models, there is still a need of standardizing the dataset and evaluation criteria (Schouten and Frasincar 2016).
Due to the high impact that non-standardized structural data can have upon a model's predictive reliability and overall reproducibility, our first task was to clean and standardize the DrugBank dataset [49 51] as described in the "Methods" section.
Although not all variables were available in all three datasets, we attempted to standardize the models across the datasets to the extent possible.
Using the COMBAT methodology described previously in Chen, C. et al., we standardized the nine datasets we combined for the training cohort (Chen et al., 2011).
To standardize these datasets as much as possible (Table 1), we selected the degrees classified with the UNESCO International Standard Classification of Education 1997 [47] (field codes 31, 42, 44, 46, 48, 52, 54, 58, and 62) as representing science and engineering degrees.
This diagnostic dataset will guide the clinical diagnosis of ELPV and will standardize the inclusion of patients into clinical trials.
To standardize the data across the six studies, some subjects included in the original analyses were excluded from the pooled dataset (Table 2-wrap>).
Standardize the testing program.
We should also standardize the voting laws.
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