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  2. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...

  3. Softmax function - Wikipedia

    en.wikipedia.org/wiki/Softmax_function

    The softmax function, also known as softargmax [1]: 184 or normalized exponential function, [2]: 198 converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression .

  4. Quantile normalization - Wikipedia

    en.wikipedia.org/wiki/Quantile_normalization

    To quantile normalize two or more distributions to each other, without a reference distribution, sort as before, then set to the average (usually, arithmetic mean) of the distributions. So the highest value in all cases becomes the mean of the highest values, the second highest value becomes the mean of the second highest values, and so on.

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The probability density, cumulative distribution, and inverse cumulative distribution of any function of one or more independent or correlated normal variables can be computed with the numerical method of ray-tracing [41] (Matlab code). In the following sections we look at some special cases.

  6. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Without normalization, the clusters were arranged along the x-axis, since it is the axis with most of variation. After normalization, the clusters are recovered as expected. In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature ...

  7. Normal matrix - Wikipedia

    en.wikipedia.org/wiki/Normal_matrix

    This is because any function of a non-defective matrix acts directly on each of its eigenvalues, and the conjugate transpose of its spectral decomposition is , where is the diagonal matrix of eigenvalues. Likewise, if two normal matrices commute and are therefore simultaneously diagonalizable, any operation between these matrices also acts on ...

  8. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    For example, CSC is (val, row_ind, col_ptr), where val is an array of the (top-to-bottom, then left-to-right) non-zero values of the matrix; row_ind is the row indices corresponding to the values; and, col_ptr is the list of val indexes where each column starts. The name is based on the fact that column index information is compressed relative ...

  9. Text normalization - Wikipedia

    en.wikipedia.org/wiki/Text_normalization

    Text normalization is the process of transforming text into a single canonical form that it might not have had before. Normalizing text before storing or processing it allows for separation of concerns, since input is guaranteed to be consistent before operations are performed on it. Text normalization requires being aware of what type of text ...