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An example of top-down processing: Even though the second letter in each word is ambiguous, top-down processing allows for easy disambiguation based on the context. These terms are also employed in cognitive sciences including neuroscience, cognitive neuroscience and cognitive psychology to discuss the flow of information in processing. [6]
Data Stream Mining (also known as stream learning) is the process of extracting knowledge structures from continuous, rapid data records.A data stream is an ordered sequence of instances that in many applications of data stream mining can be read only once or a small number of times using limited computing and storage capabilities.
Pages in category "Articles with example Python (programming language) code" The following 200 pages are in this category, out of approximately 201 total. This list may not reflect recent changes .
In computer science, an operator-precedence parser is a bottom-up parser that interprets an operator-precedence grammar.For example, most calculators use operator-precedence parsers to convert from the human-readable infix notation relying on order of operations to a format that is optimized for evaluation such as Reverse Polish notation (RPN).
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 ...
The emergence of FPGAs with enough capacity to perform complex image processing tasks also led to high-performance architectures for connected-component labeling. [20] [21] Most of these architectures utilize the single pass variant of this algorithm, because of the limited memory resources available on an FPGA. These types of connected ...
In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation: >>>
OmniMark treats input as a flow that can be scanned once, rather than as a static collection of data that supports random access. Much of an OmniMark program is in the form of condition=>action rule where the condition recognizes a length of data to be acted upon and the action specifies what is to be done with the data.