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Mansa Musa was the ruler of the Mali Empire in West Africa. Details recorded here should be sourced; unknown information is left blank.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
Indicator value is a term that is used in the ecology of plants for two different indices. The older usage of the term refers to Ellenberg's indicator values from 1974, which are based on a simple ordinal classification of plants according to the position of their realized ecological niche along an environmental gradient.[1] Since 1997, the term has also been used to refer to Dufrêne & Legendre's indicator value, which is a quantitative index measuring the statistical alliance of a species to any one of the classes in a classification of sites.[2]
Ellenberg's indicator values[1] were the first model of bioindication proposed and applied to the flora of Central Europe, and they have a long tradition in interpretation and understanding of plant communities and their evolution. The latest edition of Ellenberg's indicator values applies a 9-point scale for each of seven gradients:[3]
R - reaction (soil or water acidity/pH)
N - nitrogen (but really soil fertility or productivity, and not mineral nitrogen)
F - soil humidity or moisture
S - salt (soil salinity)
K - climatic continentality
L - light availability
T - temperature
Indicator values have also been published in 1977 by Elias Landolt for Switzerland,[4] by Mark O. Hill and others for Great Britain,[5] France (Baseflor,[citation needed] SOPHY,[6] Ecoplant) and some other floras.[citation needed]
The indicator value of Dufrêne and Legendre from 1997 is an integral part of the indicator value, which quantifies the fidelity and specificity of species in relation to groups of sites in a user-specified classification of sites, and tests for the statistical significance of the associations by permutation.[2][7][8]
The indicator value of species i for class j is obtained with the equation
Here
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Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
In statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant. It can be considered an intermediate problem between regression and classification. Examples of ordinal regression are ordered logit and ordered probit. Ordinal regression turns up often in the social sciences, for example in the modeling of human levels of preference (on a scale from, say, 1–5 for "very poor" through "excellent"), as well as in information retrieval. In machine learning, ordinal regression may also be called ranking learning.
Ambroise Marie François Joseph Palisot, Baron de Beauvois (27 July 1752, in Arras – 21 January 1820, in Paris) was a French naturalist and zoologist. Palisot collected insects in Oware, Benin, Saint Domingue, and the United States, from 1786 to 1797. Trained as a botanist, Palisot published a significant entomological paper entitled, "Insectes Receuillis en Afrique et en Amerique". Together with Frederick Valentine Melsheimer, he was one of the first entomologists to collect and describe American insects. He described many common insects and suggested an ordinal classification of insects. He described many Scarabaeidae as well as illustrating them for the first time. The study included 39 Scarabaeus species, 17 Copris species, 7 Trox species, 4 Cetonia and 4 Trichius species. Familiar beetles such as Canthon viridis, Macrodactylus angustatus and Osmoderma scabra were first described by him. Many of the specimens that were labelled from America, were from Africa, and vice versa. He created type localities in America for species such as Dynastes hercules (L.), well outside the natural range. Palisot's expeditions were described inter alia by Chase (1925) and Merrill (1937) and a summary is provided here to explain the uncertain origins of his material. Palisot trained as a lawyer but pursued postgraduate studies in botany under Jean-Baptiste Lestiboudois in Lille and Antoine Laurent de Jussieu in Paris. He also did important early work on the classification of lycopods, notably the Lycopodiaceae and Selaginellaceae.
Indicator value is a term that is used in the ecology of plants for two different indices. The older usage of the term refers to Ellenberg's indicator values from 1974, which are based on a simple ordinal classification of plants according to the position of their realized ecological niche along an environmental gradient. Since 1997, the term has also been used to refer to Dufrêne & Legendre's indicator value, which is a quantitative index measuring the statistical alliance of a species to any one of the classes in a classification of sites.
When classification is performed by a computer, statistical methods are normally used to develop the algorithm. Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features. These properties may variously be categorical (e.g. "A", "B", "AB" or "O", for blood type), ordinal (e.g. "large", "medium" or "small"), integer-valued (e.g. the number of occurrences of a particular word in an email) or real-valued (e.g. a measurement of blood pressure). Other classifiers work by comparing observations to previous observations by means of a similarity or distance function. An algorithm that implements classification, especially in a concrete implementation, is known as a classifier. The term "classifier" sometimes also refers to the mathematical function, implemented by a classification algorithm, that maps input data to a category. Terminology across fields is quite varied. In statistics, where classification is often done with logistic regression or a similar procedure, the properties of observations are termed explanatory variables (or independent variables, regressors, etc.), and the categories to be predicted are known as outcomes, which are considered to be possible values of the dependent variable. In machine learning, the observations are often known as instances, the explanatory variables are termed features (grouped into a feature vector), and the possible categories to be predicted are classes. Other fields may use different terminology: e.g. in community ecology, the term "classification" normally refers to cluster analysis.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Brown v. Board of Education in 1954.
