It is an unsupervised clustering algorithm whose objective is to group the input data into K distinct classes. The algorithm is based on defining K centroids in the dimensional space of the input data, and iteratively adjusting their positions. As a result, the data space is divided into K Voronoi cells (one per centroid), and each input observation can be associated with the nearest centroid.
5 Big Data challenges can be highlighted which are defined as V (volume, velocity, veracity, variety and value). R. Narasimhan discussed 3V with [...]
Read More »What is Digital Transformation? The industrial revolution profoundly changed the society of the 19th century, but the digital transformation of the [...]
Read More »GAMCO's forecasts point to an increase of at least 10% in the percentage of "non-performing loans" to individuals over the next five years.
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Read More »All businesses usually plan for annual growth, although not all of them achieve it. Increasing the sales of a company in 2022 is [...]
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