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  2. Errors-in-variables model - Wikipedia

    en.wikipedia.org/wiki/Errors-in-variables_model

    Linear errors-in-variables models were studied first, probably because linear models were so widely used and they are easier than non-linear ones. Unlike standard least squares regression (OLS), extending errors in variables regression (EiV) from the simple to the multivariable case is not straightforward, unless one treats all variables in the same way i.e. assume equal reliability.

  3. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values is a data format that predates personal computers by more than a decade: the IBM Fortran (level H extended) compiler under OS/360 supported CSV in 1972. [14] List-directed ("free form") input/output was defined in FORTRAN 77, approved in 1978. List-directed input used commas or spaces for delimiters, so unquoted character ...

  4. Data-driven programming - Wikipedia

    en.wikipedia.org/wiki/Data-driven_programming

    Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.

  5. JMP (statistical software) - Wikipedia

    en.wikipedia.org/wiki/JMP_(statistical_software)

    JMP can be used in conjunction with the R and Python open source programming languages to access features not available in JMP itself. [42] JMP software is partly focused on exploratory data analysis and visualization. It is designed for users to investigate data to learn something unexpected, as opposed to confirming a hypothesis.

  6. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...

  7. Generalized linear model - Wikipedia

    en.wikipedia.org/wiki/Generalized_linear_model

    Ordinary linear regression predicts the expected value of a given unknown quantity (the response variable, a random variable) as a linear combination of a set of observed values (predictors). This implies that a constant change in a predictor leads to a constant change in the response variable (i.e. a linear-response model). This is appropriate ...

  8. Flat-file database - Wikipedia

    en.wikipedia.org/wiki/Flat-file_database

    Records follow a uniform format, and there are no structures for indexing or recognizing relationships between records. The file is simple. A flat file can be a plain text file (e.g. csv, txt or tsv), or a binary file. Relationships can be inferred from the data in the database, but the database format itself does not make those relationships ...

  9. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    If the linear model is applicable, a scatterplot of residuals plotted against the independent variable should be random about zero with no trend to the residuals. [5] If the data exhibit a trend, the regression model is likely incorrect; for example, the true function may be a quadratic or higher order polynomial.

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