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  2. One-hot - Wikipedia

    en.wikipedia.org/wiki/One-hot

    An example of ordinal data would be the ratings on a test ranging from A to F, which could be ranked using numbers from 6 to 1. Since there is no quantitative relationship between nominal variables' individual values, using ordinal encoding can potentially create a fictional ordinal relationship in the data. [9] Therefore, one-hot encoding is ...

  3. Dummy variable (statistics) - Wikipedia

    en.wikipedia.org/wiki/Dummy_variable_(statistics)

    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.

  4. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    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.

  5. Encoding specificity principle - Wikipedia

    en.wikipedia.org/wiki/Encoding_specificity_principle

    The encoding specificity principle is the general principle that matching the encoding contexts of information at recall assists in the retrieval of episodic memories. It provides a framework for understanding how the conditions present while encoding information relate to memory and recall of that information.

  6. Transfer-appropriate processing - Wikipedia

    en.wikipedia.org/wiki/Transfer-appropriate...

    Transfer-appropriate processing (TAP) is a type of state-dependent memory specifically showing that memory performance is not only determined by the depth of processing (where associating meaning with information strengthens the memory; see levels-of-processing effect), but by the relationship between how information is initially encoded and how it is later retrieved.

  7. Levels of Processing model - Wikipedia

    en.wikipedia.org/wiki/Levels_of_Processing_model

    Phonemic processing includes remembering the word by the way it sounds (e.g. the word tall rhymes with fall). Lastly, we have semantic processing in which we encode the meaning of the word with another word that is similar or has similar meaning. Once the word is perceived, the brain allows for a deeper processing.

  8. Encoding (memory) - Wikipedia

    en.wikipedia.org/wiki/Encoding_(memory)

    Semantic encoding is the processing and encoding of sensory input that has particular meaning or can be applied to a context. Various strategies can be applied such as chunking and mnemonics to aid in encoding, and in some cases, allow deep processing, and optimizing retrieval.

  9. Recall (memory) - Wikipedia

    en.wikipedia.org/wiki/Recall_(memory)

    The theory of encoding specificity finds similarities between the process of recognition and that of recall. The encoding specificity principle states that memory utilizes information from the memory trace, or the situation in which it was learned, and from the environment in which it is retrieved. In other words, memory is improved when ...