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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 ...
Given the variety of data sources (e.g. databases, business applications) that provide data and formats that data can arrive in, data preparation can be quite involved and complex. There are many tools and technologies [5] that are used for data preparation. The cost of cleaning the data should always be balanced against the value of the ...
Pre-processed data Check format details in the project's worksheet. Dialog/Instruction prompted 2020 [340] Michihiro et al. Natural Instructions v2 Large dataset that covers a wider range of reasoning abilities Each task consists of input/output, and a task definition. Additionally, each ask contains a task definition.
Snippet (programming) – Small region of re-usable source code, machine code, or text; Template engine – Software designed to combine templates with a data model to produce result documents; The C preprocessor – Text processor used with C and C++ and other programming tools; The OCaml preprocessor-pretty-printer – Programming software system
A video coding format [a] (or sometimes video compression format) is a content representation format of digital video content, such as in a data file or bitstream. It typically uses a standardized video compression algorithm, most commonly based on discrete cosine transform (DCT) coding and motion compensation .
Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. [1]
Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).
Preprocessing can refer to the following topics in computer science: Preprocessor , a program that processes its input data to produce output that is used as input to another program like a compiler Data pre-processing , used in machine learning and data mining to make input data easier to work with