The phrase "a categorization strategy" is correct and usable in written English.
You can use it when discussing methods or approaches for organizing or classifying information or items.
Example: "In our research, we developed a categorization strategy to better analyze the data collected from various sources."
Alternatives: "a classification method" or "an organization approach".
A different categorization strategy may have been possible but in the absence of agreed-upon procedure, we set the SEM as the cut-off point.
A third author created a categorization scheme for comments.
Our theory is that instead of considering the specific data points and trying to find and apply a rule, our rat subjects employed what we call a similarity-based categorization strategy: Does this pattern look like the "good" targets we saw in training?
They then decided to revise the categorization strategy as follows.
They arbitrarily categorized the responses into three levels and rearranged the questionnaires into respective groups.> The discussion went on with more counter arguments against the applied categorization strategy.
First, in the categorization strategy, samples were classified as BPA-low if the BPA measurement was less than 1 ng/mL; BPA-high if BPA measurement was greater than 2 ng/mL; and BPA-intermediate for remaining samples.
While this simple categorization strategy seems to work well for yeast where it provided further mechanistic insights on such complexes, it will likely not be adequate for higher eukaryotes.
These results suggest that when high-level (labeling) categorization strategies are unavailable, adults use low-level (perceptual) strategies to categorize facial expressions.
This chapter reviews our own and others' research on multiple social categorization and discusses when and how different multiple categorization strategies can lead to more positive intergroup attitudes.
To evaluate whether different categorization strategies for introducing continuous variables in multivariable logistic regression analysis results in prognostic models that differ in content and performance.
The application of supervised text categorization strategies for requirements expressed in natural language has been proposed in several works as a method to help analysts in the detection and classification of NFRs concerning different aspects of software.
