Descriptive statistics in rapidminer

  • What is an example of a descriptive statistic?

    Descriptive statistics summarizes or describes the characteristics of a data set.
    Descriptive statistics consists of three basic categories of measures: measures of central tendency, measures of variability (or spread), and frequency distribution..

  • What is descriptive statistics in big data analytics?

    There are several ways of presenting descriptive statistics in your paper.
    These include graphs, central tendency, dispersion and measures of association tables.
    Graphs: Quantitative data can be graphically represented in histograms, pie charts, scatter plots, line graphs, sociograms and geographic information systems..

  • What is the formula for descriptive statistics?

    Descriptive analytics is the process of using current and historical data to identify trends and relationships.
    It's sometimes called the simplest form of data analysis because it describes trends and relationships but doesn't dig deeper..

  • The allowed data types are: real, integer, nominal and binominal.
    RapidMiner Radoop stores real and integer attributes in Hive as DOUBLE and BIGINT columns; nominal attributes are stored as STRING columns; binominal attributes are stored as either STRING or BOOLEAN columns.
Jun 14, 2022installation , #downloading, #rapidminer, #machine #learning, #artificial, #intelligence
Duration: 1:56
Posted: Jun 14, 2022

How does RapidMiner work?

The techniques often include calculating descriptive statistics - like mean, standard deviation, variance, or min/max - and univariate and multivariate analysis using different visualizations

Within the RapidMiner studio, we will retrieve the customer churn data

Then, we will join the output to the results and run the process

What is a time series operator in RapidMiner studio?

You are viewing the RapidMiner Studio documentation for version 9

4 - Check here for latest version This operator calculates a set of aggregated values of one or more time series

This operator calculates descriptive features (e

g sum, mean, min, max,

) of the distribution of the values of one or more time series


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