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Dummy variable (statistics) In regression analysis, a dummy variable (also known as indicator variable or just dummy) is one that takes a binary value (0 or 1) to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. [1] For example, if we were studying the relationship between biological sex and ...
Comparison of data-serialization formats. This is a comparison of data serialization formats, various ways to convert complex objects to sequences of bits. It does not include markup languages used exclusively as document file formats.
One-hot. In digital circuits and machine learning, a one-hot is a group of bits among which the legal combinations of values are only those with a single high (1) bit and all the others low (0). [1] A similar implementation in which all bits are '1' except one '0' is sometimes called one-cold. [2] In statistics, dummy variables represent a ...
A binary-to-text encoding is encoding of data in plain text. More precisely, it is an encoding of binary data in a sequence of printable characters. These encodings are necessary for transmission of data when the communication channel does not allow binary data (such as email or NNTP) or is not 8-bit clean. PGP documentation (RFC 4880) uses the ...
ASN.1. Abstract Syntax Notation One (ASN.1) is a standard interface description language (IDL) for defining data structures that can be serialized and deserialized in a cross-platform way. It is broadly used in telecommunications and computer networking, and especially in cryptography. [1]
Rather, older 8-bit encodings such as ASCII or ISO-8859-1 are still used, forgoing Unicode support entirely, or UTF-8 is used for Unicode. [citation needed] One rare counter-example is the "strings" file introduced in Mac OS X 10.3 Panther, which is used by applications to lookup internationalized versions of messages. By default, this file is ...
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks. Features are usually numeric, but other types ...
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...