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Data Binning
Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a '' bin'', are replaced by a value representative of that interval, often a central value (mean or median). It is related to quantization: data binning operates on the abscissa axis while quantization operates on the ordinate axis. Binning is a generalization of rounding. Statistical data binning is a way to group numbers of more-or-less continuous values into a smaller number of "bins". For example, if you have data about a group of people, you might want to arrange their ages into a smaller number of age intervals (for example, grouping every five years together). It can also be used in multivariate statistics, binning in several dimensions at once. In digital image processing, "binning" has a very different meaning. Pixel binning is the process of combin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Euclidean Vector
In mathematics, physics, and engineering, a Euclidean vector or simply a vector (sometimes called a geometric vector or spatial vector) is a geometric object that has magnitude (or length) and direction. Euclidean vectors can be added and scaled to form a vector space. A '' vector quantity'' is a vector-valued physical quantity, including units of measurement and possibly a support, formulated as a '' directed line segment''. A vector is frequently depicted graphically as an arrow connecting an ''initial point'' ''A'' with a ''terminal point'' ''B'', and denoted by \stackrel \longrightarrow. A vector is what is needed to "carry" the point ''A'' to the point ''B''; the Latin word means 'carrier'. It was first used by 18th century astronomers investigating planetary revolution around the Sun. The magnitude of the vector is the distance between the two points, and the direction refers to the direction of displacement from ''A'' to ''B''. Many algebraic operations on real numbe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binning (other)
Binning may refer to: People * Binning (surname) * William of Binning, 13th century Cistercian monk and abbott * Lord Binning is a subsidiary title of the Earls of Haddington; holders include: ** Charles Hamilton, Lord Binning, (1697–1732), Scottish politician ** George Baillie-Hamilton, Lord Binning, (1856–1917), British Army officer In science Binning is often used as a synonym to ''grouping'' or ''classification''. * Data binning: a data pre-processing technique. * Binning (metagenomics): the process of classifying reads into different groups or taxonomies. * Product binning: in semiconductor device fabrication, the process of categorizing finished products. * Pixel binning Pixel binning, also known as binning, is a process image sensors of digital cameras use to combine adjacent pixels throughout an image, by summing or averaging their values, during or after readout. It improves low-light performance while still al ...: the process of combining charge from adjacent ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Scikit-learn
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, ''k''-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Scikit-learn is a NumFOCUS fiscally sponsored project. Overview The scikit-learn project started as scikits.learn, a Google Summer of Code project by French data scientist David Cournapeau. The name of the project derives from its role as a "scientific toolkit for machine learning", originally developed and distributed as a third-party extension to SciPy. The original codebase was later rewritten by other developers. In 2010, contributors Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort and Vincent Michel, from the French Institute for Research in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LightGBM
LightGBM, short for Light Gradient-Boosting Machine, is a free and open source, free and open-source distributed gradient boosting, gradient-boosting framework for machine learning, originally developed by Microsoft. It is based on decision tree algorithms and used for Learning to rank, ranking, Statistical classification, classification and other machine learning tasks. The development focus is on performance and scalability. Overview The LightGBM framework supports different algorithms including GBT, GBDT, Gradient-Boosted Regression Trees, GBRT, Gradient Boosting Machine, GBM, Multiple Additive Regression Trees, MART and Random forest, RF. LightGBM has many of XGBoost's advantages, including sparse optimization, parallel training, multiple loss functions, regularization, bagging, and early stopping. A major difference between the two lies in the construction of trees. LightGBM does not grow a tree level-wise — row by row — as most other implementations do. Instead it grows t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft
Microsoft Corporation is an American multinational corporation and technology company, technology conglomerate headquartered in Redmond, Washington. Founded in 1975, the company became influential in the History of personal computers#The early 1980s and home computers, rise of personal computers through software like Windows, and the company has since expanded to Internet services, cloud computing, video gaming and other fields. Microsoft is the List of the largest software companies, largest software maker, one of the Trillion-dollar company, most valuable public U.S. companies, and one of the List of most valuable brands, most valuable brands globally. Microsoft was founded by Bill Gates and Paul Allen to develop and sell BASIC interpreters for the Altair 8800. It rose to dominate the personal computer operating system market with MS-DOS in the mid-1980s, followed by Windows. During the 41 years from 1980 to 2021 Microsoft released 9 versions of MS-DOS with a median frequen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Boosting (machine Learning)
In machine learning (ML), boosting is an Ensemble learning, ensemble metaheuristic for primarily reducing Bias–variance tradeoff, bias (as opposed to variance). It can also improve the Stability (learning theory), stability and accuracy of ML Statistical classification, classification and Regression analysis, regression algorithms. Hence, it is prevalent in supervised learning for converting weak learners to strong learners. The concept of boosting is based on the question posed by Michael Kearns (computer scientist), Kearns and Leslie Valiant, Valiant (1988, 1989):Michael Kearns(1988)''Thoughts on Hypothesis Boosting'' Unpublished manuscript (Machine Learning class project, December 1988) "Can a set of weak learners create a single strong learner?" A weak learner is defined as a Statistical classification, classifier that is only slightly correlated with the true classification. A strong learner is a classifier that is arbitrarily well-correlated with the true classification. R ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Digital Camera
A digital camera, also called a digicam, is a camera that captures photographs in Digital data storage, digital memory. Most cameras produced today are digital, largely replacing those that capture images on photographic film or film stock. Digital cameras are now widely incorporated into mobile devices like smartphones with the same or more capabilities and features of dedicated cameras. High-end, high-definition dedicated cameras are still commonly used by professionals and those who desire to take higher-quality photographs. Digital and digital movie cameras share an optical system, typically using a Camera lens, lens with a variable Diaphragm (optics), diaphragm to focus light onto an image pickup device. The diaphragm and Shutter (photography), shutter admit a controlled amount of light to the image, just as with film, but the image pickup device is electronic rather than chemical. However, unlike film cameras, digital cameras can display images on a screen immediately afte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dalton (unit)
The dalton or unified atomic mass unit (symbols: Da or u, respectively) is a unit of mass defined as of the mass of an Bound state, unbound neutral atom of carbon-12 in its nuclear and electronic ground state and invariant mass, at rest. It is a Non-SI units mentioned in the SI, non-SI unit accepted for use with SI. The word "unified" emphasizes that the definition was accepted by both IUPAP and IUPAC. The atomic mass constant, denoted , is defined identically. Expressed in terms of , the atomic mass of carbon-12: . Its value in International System of Units, SI units is an experimentally determined quantity. The 2022 CODATA recommended value of the atomic mass constant expressed in the SI base unit kilogram is:This value serves as a Conversion of units, conversion factor of mass from daltons to kilograms, which can easily be converted to Gram, grams and other metric units of mass. The 2019 revision of the SI redefined the kilogram by fixing the value of the Planck constant (), i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chemical Shift
In nuclear magnetic resonance (NMR) spectroscopy, the chemical shift is the resonant frequency of an atomic nucleus relative to a standard in a magnetic field. Often the position and number of chemical shifts are diagnostic of the structure of a molecule. Chemical shifts are also used to describe signals in other forms of spectroscopy such as photoemission spectroscopy. Some atomic nuclei possess a magnetic moment (nuclear spin), which gives rise to different energy levels and resonance frequencies in a magnetic field. The total magnetic field experienced by a nucleus includes local magnetic fields induced by currents of electrons in the molecular orbitals (electrons have a magnetic moment themselves). The electron distribution of the same type of nucleus (e.g. ) usually varies according to the local geometry (binding partners, bond lengths, angles between bonds, and so on), and with it the local magnetic field at each nucleus. This is reflected in the spin energy levels (an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pattern Recognition
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their primary function is to distinguish and create emergent patterns. PR has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use of machine learning, due to the increased availability of big data and a new abundance of processing power. Pattern recognition systems are commonly trained from labeled "training" data. When no labeled data are available, other algorithms can be used to discover previously unknown patterns. KDD and data mining have a larger focus on unsupervised methods and str ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
