subsampling Definition
the process of reducing the amount of data in a dataset by selecting a representative subset of the original data.
Using subsampling: Examples
Take a moment to familiarize yourself with how "subsampling" can be used in various situations through the following examples!
Example
Subsampling is often used to speed up machine learning algorithms.
Example
The image was subsampled to reduce its size and processing time.
Example
The audio file was subsampled to reduce its bitrate.
subsampling Synonyms and Antonyms
Synonyms for subsampling
- sampling
- decimation
- downsampling
Phrases with subsampling
a method of subsampling where the data points are selected randomly from the original dataset
Example
Random subsampling is often used in machine learning to create training and testing datasets.
stratified subsampling
a method of subsampling where the data points are selected in a way that preserves the proportion of different classes or categories in the original dataset
Example
Stratified subsampling is often used when the original dataset is imbalanced, meaning that some classes or categories have much fewer data points than others.
a method of subsampling where the data points are selected based on their importance or relevance to the problem being solved
Example
Adaptive subsampling is often used in signal processing to reduce the amount of noise in a signal while preserving its important features.
Summary: subsampling in Brief
Subsampling [sʌbˈsæmplɪŋ] is the process of reducing the amount of data in a dataset by selecting a representative subset of the original data. It is often used to speed up machine learning algorithms and reduce the size of large datasets. Subsampling can be done randomly, stratified, or adaptively, depending on the problem being solved.
