mlpack_preprocess_describe(1)

💖 mlpack_preprocess_describe — bestie edition 💖

okay so bestie, we're diving into mlpack_preprocess_describe(1), the User Commands manual page for the mlpack utility that does descriptive statistics. it's giving ✨ data girlie ✨ and i'm obsessed. let's get into it 💅

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✨ NAME ✨

mlpack_preprocess_describe — descriptive statistics, no cap 🎀

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📜 SYNOPSIS 📜

mlpack_preprocess_describe -i unknown [-d int] [-P bool] [-p int] [-r bool] [-V bool] [-w int] [-h -v]

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🌸 DESCRIPTION 🌸

so this lil utility takes a dataset and prints out the descriptive statistics of the data. and what even is descriptive statistics, you ask? it's literally the discipline of quantitatively describing the main features of a collection of information, or the quantitative description itself. periodt 💅

the program does not modify the original file, bestie — it just prints the statistics out to the console instead. the printed result will look like a table. cute, right?

optionally, the width and precision of the output can be adjusted by you, the user, using the --width (-w) and --precision (-p) parameters. a user can also select a specific dimension to analyze if there are too many dimensions. the --population (-P) parameter can be specified when the dataset should be considered as a population. otherwise, the dataset will be considered as a sample. okay slay ✨

so, a simple example where we want to print out statistical facts about the dataset X.csv using the default settings? we could run:

$ mlpack_preprocess_describe --input_file X.csv --verbose

and if we want to customize the width to 10 and precision to 5 and consider the dataset as a population, we could run:

$ mlpack_preprocess_describe --input_file X.csv --width 10 --precision 5 --verbose

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🫶 REQUIRED INPUT OPTIONS 🫶

• --input_file (-i) [unknown] — Matrix containing data, (yes bestie, you literally have to give it data, it's not optional 🙈)

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👑 OPTIONAL INPUT OPTIONS 👑

• --dimension (-d) [int] — Dimension of the data. use this to specify a dimension. default value 0.
• --help (-h) [bool] — default help info.
• --info [string] — print help on a specific option. default value ''.
• --population (-P) [bool] — if specified, the program will calculate statistics assuming the dataset is the population. by default, the program will assume the dataset as a sample.
• --precision (-p) [int] — precision of the output statistics. default value 4.
• --row_major (-r) [bool] — if specified, the program will calculate statistics across rows, not across columns. (remember that in mlpack, a column represents a point, so this option is generally not necessary. iykyk 🌈)
• --verbose (-v) [bool] — display informational messages and the full list of parameters and timers at the end of execution.
• --version (-V) [bool] — display the version of mlpack.
• --width (-w) [int] — width of the output table. default value 8.

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💜 ADDITIONAL INFORMATION 💜

for further information, including relevant papers, citations, and theory, consult the documentation found at http://www.mlpack.org or included with your distribution of mlpack. go read it bestie, it's giving academic 💀📚

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and that's the whole page, angel 🦋 this was mlpack-4.8.0, dated 22 June 2026, and the manual is mlpack_preprocess_describe(1). thanks for coming to my ted talk, mwah 💖💅✨