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2. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   For example, uncompressed songs in CD format have a data rate of 16 bits/channel x 2 channels x 44.1 kHz ≅ 1.4 Mbit/s, whereas AAC files on an iPod are typically compressed to 128 kbit/s, yielding a compression ratio of 10.9, for a data-rate saving of 0.91, or 91%.

3. KGB Archiver - Wikipedia

   en.wikipedia.org/wiki/KGB_Archiver

   Written in Visual C++ by Tomasz Pawlak, KGB Archiver is designed to achieve a very high compression ratio. It has ten levels of compression, from very weak to maximum. However, at higher compression levels, the time required to compress a file increases significantly. [3] As a consequence, the program uses memory and CPU intensively.

4. List of archive formats - Wikipedia

   en.wikipedia.org/wiki/List_of_archive_formats

   CRUNCH's implementation of LZW had a somewhat unusual feature of modifying and occasionally clearing the code table in memory when it became full, resulting in a few percent better compression on many files. .xz application/x-xz xz: Unix-like A compression format using LZMA2 to yield high compression ratios.

5. bzip2 - Wikipedia

   en.wikipedia.org/wiki/Bzip2

   bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm.It only compresses single files and is not a file archiver.It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting.

6. cloop - Wikipedia

   en.wikipedia.org/wiki/Cloop

   The data blocks are compressed separately; this makes it possible to seek to individual blocks without having to decompress the entire image from the start, but at the cost of slightly reducing the compression ratio. Live CD images typically use a block size of 256 KB as a compromise between decompression speed and space-efficiency.

7. Data compression - Wikipedia

   en.wikipedia.org/wiki/Data_compression

   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. This process condenses extensive ...