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Synthetic data is generated to meet specific needs or certain conditions that may not be found in the original, real data. One of the hurdles in applying up-to-date machine learning approaches for complex scientific tasks is the scarcity of labeled data, a gap effectively bridged by the use of synthetic data, which closely replicates real experimental data. [3]
Real GDP is an example of the distinction between real and nominal values in economics.Nominal gross domestic product is defined as the market value of all final goods produced in a geographical region, usually a country; this depends on the quantities of goods and services produced, and their respective prices.
A chained volume series is a series of economic data (such as GDP, GNP or similar kinds of data) from successive years, put in real (or constant, i.e. inflation- and deflation-adjusted) terms by computing the aggregate value of the measure (e.g. GDP or GNP) for each year using the prices of the preceding year, and then 'chain linking' the data together to obtain a time-series of figures from ...
Due to privacy reasons and data limitations and restrict observability of entire real population. Therefore, the population synthesis procedure is applied, which expands a small data sample of population by using auxiliary data, to generate a synthetic population as close as possible to the real population in its characteristics.
Real GDP can be used to calculate the GDP growth rate, which indicates how much a country's production has increased (or decreased, if the growth rate is negative) compared to the previous year, typically expressed as percentage change. The economic growth can be expressed as real GDP growth rate or real GDP per capita growth rate.
These include recommender systems, vision, language understanding, synthetic data generation search, and agentic AI. For example, xAI is adopting the GB200 to train and inference its next ...
GDP is the mean (average) wealth rather than median (middle-point) wealth. Countries with a skewed income distribution may have a relatively high per-capita GDP while the majority of its citizens have a relatively low level of income, due to concentration of wealth in the hands of a small fraction of the population. See Gini coefficient.
A common approach is to generate synthetic signals by re-arranging components of real data. Lotte [ 13 ] proposed a method of "Artificial Trial Generation Based on Analogy" where three data examples x 1 , x 2 , x 3 {\displaystyle x_{1},x_{2},x_{3}} provide examples and an artificial x s y n t h e t i c {\displaystyle x_{synthetic}} is formed ...