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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Data about cybersecurity strategies from more than 75 countries. Tokenization, meaningless-frequent words removal. [366] Yanlin Chen, Yunjian Wei, Yifan Yu, Wen Xue, Xianya Qin APT Reports collection Sample of APT reports, malware, technology, and intelligence collection Raw and tokenize data available. All data is available in this GitHub ...

  3. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.

  4. Free statistical software - Wikipedia

    en.wikipedia.org/wiki/Free_statistical_software

    Many other free to use programs were designed specifically for particular functions, like factor analysis, power analysis in sample size calculations, classification and regression trees, or analysis of missing data. Many of the free to use packages are fairly easy to learn, using menu systems. Many others are command-driven.

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, ... The characteristics of the data sample can be assessed by looking at: ... Notable free software for data analysis include:

  6. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Ploticus – software for generating a variety of graphs from raw data; PSPP – A free software alternative to IBM SPSS Statistics; R – free implementation of the S (programming language) Programming with Big Data in R (pbdR) – a series of R packages enhanced by SPMD parallelism for big data analysis; R Commander – GUI interface for R

  7. Missing data - Wikipedia

    en.wikipedia.org/wiki/Missing_data

    Generally speaking, there are three main approaches to handle missing data: (1) Imputation—where values are filled in the place of missing data, (2) omission—where samples with invalid data are discarded from further analysis and (3) analysis—by directly applying methods unaffected by the missing values. One systematic review addressing ...

  8. Multidimensional analysis - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_analysis

    In statistics, econometrics and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data set.

  9. Descriptive statistics - Wikipedia

    en.wikipedia.org/wiki/Descriptive_statistics

    More recently, a collection of summarisation techniques has been formulated under the heading of exploratory data analysis: an example of such a technique is the box plot. In the business world, descriptive statistics provides a useful summary of many types of data.