Data compression techniques geeksforgeeks

  • Lossless compression techniques

    The Lempel–Ziv (LZ) compression methods are among the most popular algorithms for lossless storage.
    DEFLATE is a variation on LZ optimized for decompression speed and compression ratio, but compression can be slow..

  • Lossy compression techniques

    There is a close connection between machine learning and compression.
    A system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression (by using arithmetic coding on the output distribution)..

Jul 27, 2021Compression reduces the cost of storage, increases the speed of algorithms, and reduces the transmission cost. Compression is achieved by 

Scholarly articles for data compression techniques geeksforgeeks

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Lossy compression methods include DCT (Discrete Cosine Transform), Vector Quantisation, and Transform Coding while Lossless compression methods include RLE (Run Length Encoding), string-table compression, LZW (Lempel Ziff Welch), and zlib.

Introduction

Data reduction is a technique used in data mining to reduce the size of a dataset while still preserving the most important information.
This can be beneficial in situations where the dataset is too large to be processed efficiently, or where the dataset contains a large amount of irrelevant or redundant information.

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What is data compression?

Data Compression is a technique in which the size of data is reduced without loss of information.
Lossy compression and Lossless compression are the categories of data compression method.

What is data compression?

Data Compression, also known as source coding, is the process of encoding or converting data in such a way that it consumes less memory space

Data compression reduces the number of resources required to store and transmit data

It can be done in two ways- lossless compression and lossy compression


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