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'''Normalized compression distance''' ('''NCD''') is a way of measuring the [[Equality (mathematics)| It can be used in [[information retrieval]] and [[data mining]] for [[cluster analysis]]. ...

{{Short description|Open-source machine learning system for end-to-end data science lifecycle}} | genre = [[Machine Learning]], [[Deep Learning]], [[Data Science]] ...

...nyi|title=The Google similarity distance|journal=IEEE Trans. Knowledge and Data Engineering|volume=19|issue=3|date=2007|pages=370–383|arxiv=cs/0412098 |doi ...07.48 |author= R.L. Cilibrasi |author2=P.M.B. Vitanyi|title= Clustering by Compression|journal=IEEE Trans. Inf. Theory|volume= 51|page=12|date=2005| doi=10.1109/T ...

...erstanding neural networks at a fundamental level. This perspective allows researchers to apply machine learning techniques directly to the weight space, enabling * [[Data augmentation]]: Developing novel augmentation techniques specific to weight ...

...es|first5=Joost|last6=Urbanik|first6=David|date=2016-10-04|title=Efficient compression of SIDH public keys|journal=Cryptology ePrint Archive |url=https://eprint.i ...khsh|author2=Jao|author3=Kalach|author4=Koziel|author5=Leonardi|title= Key Compression for Isogeny-Based Cryptosystems|website = eprint.iacr.org|access-date = 201 ...

The pressure amplitude of a wavelet can be positive (compression) or negative (decompression) and the velocity amplitude can be positive (ac ...peak at the start of systole indicating a dominant forward wave due to the compression of the left ventricle. ...

Some researchers use interval (fuzzy) measurements in statistical calculations (e.g. [http:/ == Simple example: modeling tension, compression, strain, and stress) == ...

...a=}}</ref> This version was referred as LA, which has been applied by many researchers for their optimization problems.<ref name=":0">{{Cite journal|last=Rajakuma ...|title=Multi kernel and dynamic fractional lion optimization algorithm for data clustering|url=|journal=Alexandria Engineering Journal|volume=57|issue=1|pa ...

...ing Phase Stretch Transform.png|thumb|Feature detection on 1-D time domain data using phase stretch transform.]] ...al images. PST can be applied to digital images and temporal (time series) data. It is a physics-based feature engineering algorithm.<ref>Physics-based Fea ...

...and Gnirk.<ref name=cheatham>Cheatham and Gnirk (1966).</ref> Test using compression and tension show necking of rock specimens while tests using [[wedge penetr ...ct of temperature on rock plasticity has been explored by several teams of researchers.<ref>Griggs, Turner, Heard (1960)</ref> It is observed that the peak stres ...

...hm]]). Though ''PCM'' is a more general term, it is often used to describe data encoded as LPCM. ...to-digital converter]].<ref>U.S. patent number 1,608,527; also see p. 8, ''Data conversion handbook'', Walter Allan Kester, ed., Newnes, 2005, {{ISBN|0-750 ...

...ke as input a [[string (computer science)|string]] and produce a [[Boolean data type|Boolean]] output, i.e. either "accept" or "reject". In contrast, weigh ...e=16|issue=1|pages=69–88|doi=10.1006/csla.2001.0184|issn=0885-2308}}</ref> Researchers have studied weighted automata from the perspective of [[machine learning|l ...

...s|regression]], [[Cluster analysis|clustering]], [[sparse approximation]], compression and [[feature learning]] with a single layer or multiple layers of hidden n According to some researchers, these models are able to produce good generalization performance and learn ...

[[Filter bank]]s has different usage in many areas, such as signal and image compression, and processing. ...during the processing, transmission and reception. In order to reduce the data to be processed, save storage and lower the complexity, multirate sampling ...

...mbinator.com/item?id=38654038 |archive-date=24 December 2023}}</ref> Other researchers helped analyse and explain the algorithm.<ref name="explain">{{cite arXiv | ...stText]] project showed that word2vec is superior when trained on the same data.<ref>{{cite arXiv |eprint=1607.01759 |class=cs.CL |first1=Armand |last1=Jou ...

...amplification: An efficient way to train deep neural networks|journal=Big Data Mining and Analytics|volume=3|issue=3|pages=198|doi=10.26599/BDMA.2020.9020 Backpropagation allowed researchers to train [[Supervised learning|supervised]] deep artificial neural networks ...

...k prediction models, i.e., models that make very few assumptions about the data, which are typically simple [[Decision tree learning|decision tree]]s.<ref ...tween up to two variables, and so on. <math>J</math> can be adjusted for a data set at hand. ...

...011 | title = Practical measures of integrated information for time-series data | journal = PLOS Comput. Biol. | volume = 7 | issue = 1| page = e1001052 | ...i^{\textrm{Max}}</math> can readily be computed for smaller sets of neural data. Moreover, matching IIT's predictions, <math>\Phi^{\textrm{Max}}</math>was ...

...|url=https://eng.famu.fsu.edu/news/low-gravity-simulator-design-developed-researchers-offers-new-avenues-space-research |access-date=2024-08-08 |website=eng.famu ...14 |pmid=19727328|bibcode=2008AcAau..63..594K }}</ref> These flights allow researchers to conduct hands-on experiments and test equipment destined for space missi ...

...ic bias|biases]] present in the [[Training, validation, and test data sets|data]] they are trained in.<ref name="Manning-2022">{{cite journal |last=Manning ...|first3=Fernando |date=March 2009 |title=The Unreasonable Effectiveness of Data |url=https://ieeexplore.ieee.org/document/4804817 |journal=IEEE Intelligent ...