An efficient method for compression of behavioral data is presented in this paper. The data sets, which occurs most in a wide variety of applications, create some of the most significant challenges in ...

A two dimensional data matrix has been widely used in many applications. The lossless compression of data matrix not only brings benefits for storage but also for network transmission. In this paper, ...

Learn how to understand, choose, implement, evaluate, and communicate clustering algorithms and results in data mining interviews.

Mastering-Image-Compression-with-K-means-Clustering Introduction: In the vast realm of machine learning and data science, the K-means algorithm stands as a stalwart technique for clustering data into ...

In his article "Context binning, model clustering and adaptivity for data compression of genetic data", Jarek Duda proposes promising compression techniques that should help build a compressor better ...

What is K-Means Clustering? Clustering is a grouping of different data points which are similar to each other and form different groups which contain similar data points. For example, if we are having ...

Rapid development of high-throughput toxicogenomics technologies has created new approaches to screen environmental samples for mechanistic toxicity assessment. However, challenges remain in the ...