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2. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   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:

3. List of archive formats - Wikipedia

   en.wikipedia.org/wiki/List_of_archive_formats

   Genozip, a compressor for genomic file formats such as FASTQ, BAM, VCF and others. [4].gz application/gzip [5] gzip: Unix-like GNU Zip, the primary compression format used by Unix-like systems. The compression algorithm is Deflate, which combines LZSS with Huffman coding. .lz application/x-lzip lzip: Unix-like

4. 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.

5. Deflate - Wikipedia

   en.wikipedia.org/wiki/DEFLATE

   What has changed is the increase in dictionary size from 32 KB to 64 KB, an extension of the distance codes to 16 bits so that they may address a range of 64 KB, and the length code, which is extended to 16 bits so that it may define lengths of three to 65,538 bytes. [6]

6. PDF - Wikipedia

   en.wikipedia.org/wiki/PDF

   Portable Document Format (PDF), standardized as ISO 32000, is a file format developed by Adobe in 1992 to present documents, including text formatting and images, in a manner independent of application software, hardware, and operating systems.

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.