Search results
Results From The WOW.Com Content Network
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space .
In later work, his research group, together with Carl D Christensen and Johann Rohwer, developed a Python based tool called SymCA that was part of the PySCeSToolbox toolkit [3] [4] that could generate patterns automatically and symbolically from a description of the network. This software was used to generate the patterns shown below.
In chunked transfer encoding, the data stream is divided into a series of non-overlapping "chunks". The chunks are sent out and received independently of one another. No knowledge of the data stream outside the currently-being-processed chunk is necessary for both the sender and the receiver at any given time.
In data deduplication, data synchronization and remote data compression, Chunking is a process to split a file into smaller pieces called chunks by the chunking algorithm. It can help to eliminate duplicate copies of repeating data on storage, or reduces the amount of data sent over the network by only selecting changed chunks.
The weighted product model (WPM) is a popular multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM) method. It is similar to the weighted sum model (WSM) in that it produces a simple score, but has the very important advantage of overcoming the issue of 'adding apples and pears' i.e. adding together quantities measured in different units.
A chunk is a fragment of information which is used in many multimedia file formats, such as PNG, IFF, MP3 and AVI. [1] Each chunk contains a header which indicates some parameters (e.g. the type of chunk, comments, size etc.). Following the header is a variable area containing data, which is decoded by the program from the parameters in the ...
High dimensional data can be hard for machines to work with, requiring significant time and space for analysis. It also presents a challenge for humans, since it's hard to visualize or understand data in more than three dimensions.
Methyl cyanoacrylate (MCA; also sometimes referred to as α-cyanoacrylate or alpha-cyanoacrylate) [3] is an organic compound that contains several functional groups: a methyl ester, a nitrile, and an alkene. It is a colorless liquid with low viscosity. Its chief use is as the main component of cyanoacrylate glues.