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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 ...
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 ...
Feature hashing. In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features, i.e. turning arbitrary features into indices in a vector or matrix. [1][2] It works by applying a hash function to the features and using their hash values as indices ...
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]
The main reason for using this positional encoding function is that using it, shifts are linear transformations: (+) = (()) where is the distance one wishes to shift. This allows the transformer to take any encoded position, and find the encoding of the position n-steps-ahead or n-steps-behind, by a matrix multiplication.
Categorical variable. In statistics, a categorical variable (also called qualitative variable) is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property. [ 1 ]
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
t. e. Asymmetric numeral systems (ANS) [1][2] is a family of entropy encoding methods introduced by Jarosław (Jarek) Duda [3] from Jagiellonian University, used in data compression since 2014 [4] due to improved performance compared to previous methods. [5] ANS combines the compression ratio of arithmetic coding (which uses a nearly accurate ...