grade estimation - traducción al ruso
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grade estimation - traducción al ruso

CONSTRUCTION OF AN ESTIMATE, BASED ON OBSERVED DATA, OF AN UNOBSERVABLE UNDERLYING PROBABILITY DENSITY FUNCTION
Density Estimation; Probability estimation; Probability density estimation
  • Estimated probability of ''p'' (diabetes=1 | glu)
  • Histogram and density function for a Gumbel distribution <ref>[https://www.waterlog.info/cumfreq.htm A calculator for probability distributions and density functions]</ref>
  • Demonstration of density estimation using [[Kernel density estimation]]: The true density is mixture of two Gaussians centered around 0 and 3, shown with solid blue curve. In each frame, 100 samples are generated from the distribution, shown in red. Centered on each sample, a Gaussian kernel is drawn in gray. Averaging the Gaussians yields the density estimate shown in the dashed black curve.
  • Estimated probability of ''p''(diabetes=1 &#124; glu)
  • Estimated density of ''p'' (glu &#124; diabetes=1) (red), ''p''&nbsp;(glu &#124; diabetes=0) (blue), and ''p''&nbsp;(glu) (black)

grade estimation      
оценка качества; определение сорта
evolutionary grade         
  • The genus ''[[Australopithecus]]'' is ancestral to ''[[Homo]]'', yet actively in use in [[palaeoanthropology]].
NON-MONOPHYLETIC GROUPING OF ORGANISMS UNITED BY MORPHOLOGICAL OR PHYSIOLOGICAL CHARACTERISTICS
Grade (biology); Grade (evoltuion); Grade (evolution); Grade (taxonomy); Grade (cladistics); Grade(Taxonomy)

общая лексика

эволюционная ступень

first-grade         
FIRST GRADE IN ELEMENTARY SCHOOL
1st grade; First-grade; First Grade; Grade one; 1st Grade; Grade 1

общая лексика

первосортный

Definición

O grade

Wikipedia

Density estimation

In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population.

A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization. The most basic form of density estimation is a rescaled histogram.

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