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  2. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow ...

  3. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text , where each line of the file typically represents one data record .

  4. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    In the rectilinear TSP, the distance between two cities is the sum of the absolute values of the differences of their x- and y-coordinates. This metric is often called the Manhattan distance or city-block metric. In the maximum metric, the distance between two points is the maximum of the absolute values of differences of their x- and y ...

  5. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    For example, many classifiers calculate the distance between two points by the Euclidean distance. If one of the features has a broad range of values, the distance will be governed by this particular feature. Therefore, the range of all features should be normalized so that each feature contributes approximately proportionately to the final ...

  6. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    Compute significance between two correlations, for the comparison of two correlation values. "A MATLAB Toolbox for computing Weighted Correlation Coefficients". Archived from the original on 24 April 2021. Proof that the Sample Bivariate Correlation has limits plus or minus 1

  7. Spearman's rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Spearman's_rank_correlation...

    Intuitively, the Spearman correlation between two variables will be high when observations have a similar (or identical for a correlation of 1) rank (i.e. relative position label of the observations within the variable: 1st, 2nd, 3rd, etc.) between the two variables, and low when observations have a dissimilar (or fully opposed for a ...

  8. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The column space of a matrix is the image or range of the corresponding matrix transformation. Let be a field. The column space of an m × n matrix with components from is a linear subspace of the m-space. The dimension of the column space is called the rank of the matrix and is at most min(m, n). [1]

  9. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    The Pandas and Polars Python libraries implement the Pearson correlation coefficient calculation as the default option for the methods pandas.DataFrame.corr and polars.corr, respectively. Wolfram Mathematica via the Correlation function, or (with the P value) with CorrelationTest. The Boost C++ library via the correlation_coefficient function.