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Traducción y análisis de palabras por inteligencia artificial ChatGPT
En esta página puede obtener un análisis detallado de una palabra o frase, producido utilizando la mejor tecnología de inteligencia artificial hasta la fecha:
- cómo se usa la palabra
- frecuencia de uso
- se utiliza con más frecuencia en el habla oral o escrita
- opciones de traducción
- ejemplos de uso (varias frases con traducción)
- etimología
Qué (quién) es unexplained variance - definición
STATISTICAL NOISE
Statistical noise; Unexplained variance; FVU
Fraction of variance unexplained
In statistics, the fraction of variance unexplained (FVU) in the context of a regression task is the fraction of variance of the regressand (dependent variable) Y which cannot be explained, i.e.
Medically unexplained physical symptoms
SYMPTOMS WITH NO KNOWN OR AGREED UPON CAUSE
Medically Unexplained Physical Symptoms; Medically unexplained symptoms; Medically unexplained syndrome
Medically unexplained physical symptoms (MUPS or MUS) are symptoms for which a treating physician or other healthcare providers have found no medical cause, or whose cause remains contested. In its strictest sense, the term simply means that the cause for the symptoms is unknown or disputed—there is no scientific consensus.
Bias–variance tradeoff
PROPERTY OF A SET OF PREDICTIVE MODELS WHEREBY MODELS WITH A LOWER BIAS IN PARAMETER ESTIMATION HAVE A HIGHER VARIANCE OF THE PARAMETER ESTIMATES ACROSS SAMPLES, AND VICE VERSA
Bias variance; Bias-variance tradeoff; Bias-variance dilemma; Bias–variance dilemma; Bias-variance decomposition; Bias–variance decomposition; Bias and variance tradeoff; Bias--variance tradeoff
In statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters.
Wikipedia
Fraction of variance unexplained
In statistics, the fraction of variance unexplained (FVU) in the context of a regression task is the fraction of variance of the regressand (dependent variable) Y which cannot be explained, i.e., which is not correctly predicted, by the explanatory variables X.
