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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.
One-hot encoding is often used for indicating the state of a state machine.When using binary, a decoder is needed to determine the state. A one-hot state machine, however, does not need a decoder as the state machine is in the nth state if, and only if, the nth bit is high.
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.
State-dependent memory is one example of encoding specificity. If an individual encodes information while intoxicated he or she, ideally, should match that state when attempting to recall the encoded information. This type of state-dependent effect is strongest with free recall rather than when strong retrieval cues are present. [16]
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.
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.
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 ...
Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio.