Browse Definitions :
Definition

over sampling and under sampling

Contributor(s): Matthew Haughn

Over sampling and under sampling are techniques used in data mining and data analytics to modify unequal data classes to create balanced data sets. Over sampling and under sampling are also known as resampling.

These data analysis techniques are often used to be more representative of real world data. For example, data adjustments can be made in order to provide balanced training materials for AI and machine learning algorithms.

One area where over sampling and under sampling techniques are used is for survey research. A survey sample population may be unbalanced in terms of types of participants, which can deter the larger population that the survey is meant to study. By using over or under sampling, the ratios of surveyed characteristics, such as gender, age group and ethnicity, can used to make the weight of the data better representative of the group’s ratios within the greater populations.

Over sampling vs. under sampling

When one class of data is the underrepresented minority class in the data sample, over sampling techniques maybe used to duplicate these results for a more balanced amount of positive results in training. Over sampling is used when the amount of data collected is insufficient. A popular over sampling technique is SMOTE (Synthetic Minority Over-sampling Technique), which creates synthetic samples by randomly sampling the characteristics from occurrences in the minority class.

Conversely, if a class of data is the overrepresented majority class, under sampling may be used to balance it with the minority class. Under sampling is used when the amount of collected data is sufficient. Common methods of under sampling include cluster centroids and Tomek links, both of which target potential overlapping characteristics within the collected data sets to reduce the amount of majority data.

In both over sampling and under sampling, simple data duplication is rarely suggested. Generally, over sampling is preferable as under sampling can result in the loss of important data. Under sampling is suggested when the amount of data collected is larger than ideal and can help data mining tools to stay within the limits of what they can effectively process.

This was last updated in November 2018

Continue Reading About over sampling and under sampling

Start the conversation

Send me notifications when other members comment.

Please create a username to comment.

-ADS BY GOOGLE

File Extensions and File Formats

SearchCompliance

  • compliance audit

    A compliance audit is a comprehensive review of an organization's adherence to regulatory guidelines.

  • regulatory compliance

    Regulatory compliance is an organization's adherence to laws, regulations, guidelines and specifications relevant to its business...

  • Whistleblower Protection Act

    The Whistleblower Protection Act of 1989 is a law that protects federal government employees in the United States from ...

SearchSecurity

  • Transport Layer Security (TLS)

    Transport Layer Security (TLS) is a protocol that provides authentication, privacy, and data integrity between two communicating ...

  • van Eck phreaking

    Van Eck phreaking is a form of electronic eavesdropping that reverse engineers the electromagnetic fields (EM fields) produced by...

  • zero-trust model (zero trust network)

    The zero trust model is a security model used by IT professionals that requires strict identity and device verification ...

SearchHealthIT

SearchDisasterRecovery

  • cloud insurance

    Cloud insurance is any type of financial or data protection obtained by a cloud service provider. 

  • business continuity software

    Business continuity software is an application or suite designed to make business continuity planning/business continuity ...

  • business continuity policy

    Business continuity policy is the set of standards and guidelines an organization enforces to ensure resilience and proper risk ...

SearchStorage

  • solid-state storage

    Solid-state storage (SSS) is a type of computer storage media made from silicon microchips. SSS stores data electronically ...

  • persistent storage

    Persistent storage is any data storage device that retains data after power to that device is shut off. It is also sometimes ...

  • computational storage

    Computational storage is an information technology (IT) architecture in which data is processed at the storage device level to ...

Close