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Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
In fact, if we consider files of length N, if all files were equally probable, then for any lossless compression that reduces the size of some file, the expected length of a compressed file (averaged over all possible files of length N) must necessarily be greater than N. [citation needed] So if we know nothing about the properties of the data ...
While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space [5] – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better ...
File size is a measure of how much data a computer file contains or how much storage space it is allocated. Typically, file size is expressed in units based on byte . A large value is often expressed with a metric prefix (as in megabyte and gigabyte ) or a binary prefix (as in mebibyte and gibibyte ).
Components and libraries for Web applications and websites have been developed to optimize file requests and reduce page load times by shrinking the size of various files. JavaScript and Cascading Style Sheet (CSS) resources may be minified, preserving their behavior while considerably reducing their file size. Libraries available online are ...
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