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  • Concepts
  • 1 peces versty Concepts peces Rchness peces-area Curves versty Indces - mpson's Index - hannon-wener Index - rlloun Index peces Abundance Models escrbng Communtes There are two mportant descrptors of a communty: ) ts physognomy (physcal structure), as descrbed n the prevous lecture, and ) the number of speces present and ther relatve abundances (speces rchness and dversty). (docplayer.net)
  • integral calculus
  • This applet allows the user to learn visually and numerically understand how the subdivided rectangles under a curve of a function can converge to (reach) the exact value of area calculated with integral calculus methods by increasing the number of subdivisions to close to the infinite limit. (geogebra.org)
  • While integral calculus techniques can be applied to find an area under the normal curve, we shall judiciously not attempt to do so. (oreilly.com)
  • sensitivity
  • The ROC curve is thus the sensitivity as a function of fall-out . (wikipedia.org)
  • The area under the entire curve (AUC) is one of the most commonly used summary indices in receiver operating characteristic (ROC) analysis and can be interpreted as the average value of sensitivity for all possible values of specificity [ 1 ]. (hindawi.com)
  • rectangle
  • But the calculation would be exactly the same if you were calculating the area of the rectangle and subtract area A. So it seems silly not to use this method and do use the above method. (physicsforums.com)
  • estimation
  • Maximum likelihood estimation of receiver operating characteristic (ROC) curves using the "proper" binormal model can be interpreted in terms of Bayesian estimation as assuming a flat joint prior distribution on the c and d a parameters. (spie.org)
  • Estimation of the minimal area from the curve is necessarily subjective, so some authors prefer to define minimal area as the area enclosing at least 95 percent (or some other large proportion) of the total species found. (wikipedia.org)
  • metric
  • The detection performance is characterized by the area under the Receiver Operating Characteristic (ROC) Curve (AUC), which is a simple statistical performance measuring metric that varies between 0.5 and 1. (techrepublic.com)
  • Includes standard vector algebra, vector analysis, introduction to tensor fields and Riemannian manifolds, geodesic curves, curvature tensor and general relativity to Schwarzschild metric. (wikipedia.org)
  • Different
  • Different shapes of the ROC curves, false positive fraction ranges, and sample size configurations were considered. (hindawi.com)
  • Larger islands contain larger habitat areas and opportunities for more different varieties of habitat. (wikipedia.org)
  • Then applying different sampling methods will lead to different sets of individuals being observed for the same area of interest, and the species richness of each set may be different. (wikipedia.org)
  • Such curves can be constructed in different ways. (wikipedia.org)
  • Michael Rosenzweig also notes that species-area relationships for very large areas-those collecting different biogeographic provinces or continents-behave differently from species-area relationships from islands or smaller contiguous areas. (wikipedia.org)
  • Species-area relationships are often graphed for islands (or habitats that are otherwise isolated from one another, such as woodlots in an agricultural landscape) of different sizes. (wikipedia.org)
  • diagram
  • The finite region R 2 is below the curve and the line and is bounded by the positive x - and y -axes as shown in the diagram. (mathhelpforum.com)
  • Results
  • This is done by plotting the curve (usually on arithmetic axes, not log-log or semilog axes), and estimating the area after which using larger quadrats results in the addition of only a few more species. (wikipedia.org)
  • commonly
  • An ROC curve is the most commonly used way to visualize the performance of a binary classifier , and AUC is (arguably) the best way to summarize its performance in a single number . (dataschool.io)
  • An ROC curve is a commonly used way to visualize the performance of a binary classifier , meaning a classifier with two possible output classes. (dataschool.io)
  • Leads
  • The theory assumes that speciation rates are constant with area, and a lower extinction rate coupled with higher speciation leads to more species. (wikipedia.org)