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The scikit-multiflow library is implemented under the open research principles and is currently distributed under the BSD 3-clause license. scikit-multiflow is mainly written in Python, and some core elements are written in Cython for performance. scikit-multiflow integrates with other Python libraries such as Matplotlib for plotting, scikit-learn for incremental learning methods [4 ...
In connection-oriented communication, a data stream is the transmission of a sequence of digitally encoded signals to convey information. [1] Typically, the transmitted symbols are grouped into a series of packets. [2] Data streaming has become ubiquitous. Anything transmitted over the Internet is transmitted as a data stream
The previous algorithm describes the first attempt to approximate F 0 in the data stream by Flajolet and Martin. Their algorithm picks a random hash function which they assume to uniformly distribute the hash values in hash space. Bar-Yossef et al. in [10] introduced k-minimum value algorithm for determining number of distinct elements in data ...
RapidMiner: commercial software for knowledge discovery, data mining, and machine learning also featuring data stream mining, learning time-varying concepts, and tracking drifting concept (if used in combination with its data stream mining plugin (formerly: Concept Drift plugin)) RiverML: River is a Python library for online machine learning ...
Stream processing is essentially a compromise, driven by a data-centric model that works very well for traditional DSP or GPU-type applications (such as image, video and digital signal processing) but less so for general purpose processing with more randomized data access (such as databases). By sacrificing some flexibility in the model, the ...
In computer science, data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data, financial transactions etc. Data stream clustering is usually studied as a streaming algorithm and the objective is, given a sequence of points, to construct a good clustering of the stream, using a small amount of memory and time.
Stream processing — in parallel processing, especially in graphic processing, the term stream is applied to hardware as well as software. There it defines the quasi-continuous flow of data that is processed in a dataflow programming language as soon as the program state meets the starting condition of the stream.
A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. [1] A key concept of the system is the graph (or edge or relationship). The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships ...