Misclassification: meaning, definitions and examples
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misclassification
[ mɪsˌklæsɪfɪˈkeɪʃən ]
data analysis
Misclassification refers to the incorrect assignment of a category or label to an instance or observation. It can occur in various domains such as machine learning, statistics, and data analysis, leading to inaccurate predictions or insights.
Synonyms
error, inaccuracy, mislabeling, mistake
Examples of usage
- The misclassification of data points affected the model's accuracy.
- Due to misclassification, the survey results were misleading.
- The study examined the impact of misclassification on epidemiological research.
legal context
In a legal context, misclassification can happen when an employee is wrongly classified as an independent contractor, leading to potential implications for benefits and taxes. This often results in disputes and legal challenges.
Synonyms
misidentification, misrepresentation
Examples of usage
- The company faced lawsuits due to employee misclassification.
- Misclassification of workers can lead to serious tax implications.
- The lawyer argued that the misclassification violated labor laws.
Translations
Translations of the word "misclassification" in other languages:
🇵🇹 classificação incorreta
🇮🇳 गलत वर्गीकरण
🇩🇪 Fehlklassifizierung
🇮🇩 klasifikasi yang salah
🇺🇦 неправильна класифікація
🇵🇱 błędna klasyfikacja
🇯🇵 誤分類
🇫🇷 mauvaise classification
🇪🇸 clasificación incorrecta
🇹🇷 yanlış sınıflandırma
🇰🇷 잘못된 분류
🇸🇦 تصنيف خاطئ
🇨🇿 chybná klasifikace
🇸🇰 nesprávna klasifikácia
🇨🇳 错误分类
🇸🇮 napačna klasifikacija
🇮🇸 rangfærsluvilla
🇰🇿 қате жіктеу
🇬🇪 არასწორი კლასიფიკაცია
🇦🇿 səhv təsnifat
🇲🇽 clasificación incorrecta
Etymology
The term 'misclassification' is derived from the prefix 'mis-', which indicates a wrong or mistaken action, combined with the word 'classification', referring to the process of categorizing or grouping items based on shared characteristics. The prefix 'mis-' has its origins in Old English, meaning 'wrongly' or 'badly'. The word 'classification' comes from the Latin root 'classis', which means 'class' or 'division'. The concept of classification itself evolved with the development of various fields, including biology, sociology, and data science, leading to the need to systematically categorize information or entities. As data became increasingly complex and abundant, particularly with the rise of computing and machine learning, the term evolved to specifically address the errors that arise in these processes, particularly where automated systems are used to make predictions based on categorized data.