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For example, if we were studying the relationship between biological sex and income, we could use a dummy variable to represent the sex of each individual in the study. The variable could take on a value of 1 for males and 0 for females (or vice versa). In machine learning this is known as one-hot encoding.
The vector consists of 0s in all cells with the exception of a single 1 in a cell used uniquely to identify the word. One-hot encoding ensures that machine learning does not assume that higher numbers are more important. For example, the value '8' is bigger than the value '1', but that does not make '8' more important than '1'.
Examples of categorical features include gender, color, and zip code. Categorical features typically need to be converted to numerical features before they can be used in machine learning algorithms. This can be done using a variety of techniques, such as one-hot encoding, label encoding, and ordinal encoding.
In a typical document classification task, the input to the machine learning algorithm (both during learning and classification) is free text. From this, a bag of words (BOW) representation is constructed: the individual tokens are extracted and counted, and each distinct token in the training set defines a feature (independent variable) of each of the documents in both the training and test sets.
Some older and today uncommon formats include BOO, BTOA, and USR encoding. Most of these encodings generate text containing only a subset of all ASCII printable characters: for example, the base64 encoding generates text that only contains upper case and lower case letters, (A–Z, a–z), numerals (0–9), and the "+", "/", and "=" symbols.
Shown here is another possible encoding; XML schema does not define an encoding for this datatype. ^ The RFC CSV specification only deals with delimiters, newlines, and quote characters; it does not directly deal with serializing programming data structures.
ASN.1 is a data type declaration notation. It does not define how to manipulate a variable of such a type. Manipulation of variables is defined in other languages such as SDL (Specification and Description Language) for executable modeling or TTCN-3 (Testing and Test Control Notation) for conformance testing.
This page was last edited on 17 November 2006, at 00:14 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.