Preshrank: meaning, definitions and examples
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preshrank
[ preʃræŋk ]
data processing
To preshrank means to reduce the size or dimensions of a dataset, often by removing redundancies or irrelevant information prior to a more thorough analysis. This process is essential in fields like data science and statistics, where handling large datasets can lead to inefficiencies. By preshrinking data, one can ensure that subsequent analyses are more focused and manageable. This term is commonly used in the context of preparing data for machine learning models or statistical testing.
Synonyms
Examples of usage
- We need to preshrank the dataset before running the regression analysis.
- Preshrinking the data helped us reduce computation time significantly.
- The team decided to preshrank the images to improve loading speeds.
Translations
Translations of the word "preshrank" in other languages:
🇵🇹 pré-encolhido
🇮🇳 पूर्व-संकुचित
🇩🇪 vorgeschrumpft
🇮🇩 pra-padat
🇺🇦 попередньо зменшений
🇵🇱 wstępnie skurczony
🇯🇵 プレシュランク
🇫🇷 pré-rétréci
🇪🇸 pre-encogido
🇹🇷 önceden büzülmüş
🇰🇷 사전 수축
🇸🇦 مسبق الانكماش
🇨🇿 předpředený
🇸🇰 predzmrštený
🇨🇳 预收缩
🇸🇮 predshrunk
🇮🇸 forskrúðinn
🇰🇿 алдын ала қысылған
🇬🇪 წინასწარ შეკუმშული
🇦🇿 əvvəlcədən sıxılmış
🇲🇽 pre-encogido
Etymology
The term 'preshrank' is derived from the prefix 'pre-' meaning 'before' and 'shrink', which originates from Old English 'scrincan', meaning 'to become smaller, to shrink'. Over time, the concept of data handling has evolved, and terms like 'shrink' have been adopted in various fields, notably in data science and statistics. As the amount of data generated has exponentially increased, the need for effective data management solutions has grown. Consequently, new terminologies like 'preshrink' have emerged to describe the process of preparing data for analysis in modern computing. The integration of technology and language has continuously shaped how we describe our actions, especially in technical fields.