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The areas indicated in the previous section as GBK/1 and GBK/2, taken by themselves, is simply GB 2312-80 in its usual encoding, GBK/1 being the non-hanzi region and GBK/2 the hanzi region. GB 2312, or more properly the EUC-CN encoding thereof, takes a pair of bytes from the range A1 – FE , like any 94² ISO-2022 character set loaded into GR.
Punched tape with the word "Wikipedia" encoded in ASCII.Presence and absence of a hole represents 1 and 0, respectively; for example, W is encoded as 1010111.. Character encoding is the process of assigning numbers to graphical characters, especially the written characters of human language, allowing them to be stored, transmitted, and transformed using computers. [1]
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
This can be done using a variety of techniques, such as one-hot encoding, label encoding, and ordinal encoding. The type of feature that is used in feature engineering depends on the specific machine learning algorithm that is being used. Some machine learning algorithms, such as decision trees, can handle both numerical and categorical features.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
Since GBK is a superset of EUC-CN (although not itself an EUC code) and superseded GB 2312 long ago, and since Microsoft software continued to assign the GB2312 encoding label to code page 936 even after extending it to implement GBK rather than EUC-CN, most modern-day Windows-based software products mean partial support for GBK via Windows-936 ...
Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare transfer learning). [1] In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed ...
This article includes a list of general references, but it lacks sufficient corresponding inline citations. Please help to improve this article by introducing more precise citations. (July 2019) (Learn how and when to remove this message) This article compares Unicode encodings in two types of environments: 8-bit clean environments, and environments that forbid the use of byte values with the ...