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undersampling

undersampling
Danh từ

This term is primarily used in technical domains, specifically machine learning and digital signal processing. In data science, it describes a strategic reduction of data to combat class imbalance, ensuring a model does not simply memorize the most frequent outcome. It is often contrasted with oversampling, where the minority class is artificially increased.

In the context of signal processing, the term carries a negative connotation of error or failure. Here, it refers to a technical mistake where the sampling frequency is insufficient to capture the original signal accurately, leading to aliasing—a distortion where high-frequency components are incorrectly mapped to lower frequencies.

Ý nghĩa

Danh từundersampling

The process of reducing the number of examples in the majority class of a dataset to balance the class distribution for machine learning.

The data scientist used undersampling to prevent the model from being biased toward the majority class.

Danh từundersampling

The act of sampling a signal at a rate lower than the Nyquist rate, resulting in aliasing.

The audio distortion was caused by undersampling during the analog-to-digital conversion process.

Từ liên quan

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Last Updated: May 2026Report an Error