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Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
Ñ-shaped animation showing flags of some countries and territories where Spanish is spoken. Spanish is the official language (either by law or de facto) in 20 sovereign states (including Equatorial Guinea, where it is official but not a native language), one dependent territory, and one partially recognized state, totaling around 442 million people.
A language that uniquely represents the national identity of a state, nation, and/or country and is so designated by a country's government; some are technically minority languages. (On this page a national language is followed by parentheses that identify it as a national language status.) Some countries have more than one language with this ...
Warning sign at the fence of a military area in Turkey, in Turkish, English, French and German. A bilingual sign (or, by extension, a multilingual sign) is the representation on a panel (sign, usually a traffic sign, a safety sign, an informational sign) of texts in more than one language.
The Organization of Ibero-American States also includes Spanish-speaking Equatorial Guinea, in Central Africa, [1] [2] but not the Portuguese-speaking African countries. The Latin Recording Academy , the organization responsible for the Latin Grammy Awards , also includes Spain and Portugal as well as the Latino population of Canada and the ...
Sparse principal component analysis (SPCA or sparse PCA) is a technique used in statistical analysis and, in particular, in the analysis of multivariate data sets. It extends the classic method of principal component analysis (PCA) for the reduction of dimensionality of data by introducing sparsity structures to the input variables.
Modes of variation provide a visualization of this decomposition and an efficient description of variation around the mean. Both in principal component analysis (PCA) and in functional principal component analysis (FPCA), modes of variation play an important role in visualizing and describing the variation in the data contributed by each ...
The peso is the monetary unit of several Spanish-speaking countries in Latin America, as well as the Philippines. Originating in the Spanish Empire, the word peso translates to "weight". In most countries of the Americas, the symbol commonly known as dollar sign, "$", was originally used as an abbreviation of "pesos" and later adopted by the ...