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03_​Continuous_​Distribution

This component identifies the five best-fitting continuous probability distributions for numeric columns using Python’s Fitter library.

It supports 80 different continuos probability distributions and plots the best five distributions and probabily plot based on the least sum of squared errors.

The component configuration window allows to select the input colomn(s) to fit the distribution. The Python's library behind the component is able to handle datasets of max 10K rows. Larger datasets will be downsampled to 10K rows.

The result of the component comprises a table with the five best fit distributions, probability plots, and a table with descriptive stats for the selected column(s).

URL: Know Your Data with Continuous Probability Distribution (theory) https://www.knime.com/blog/learn-continuous-probability-distribution
URL: Identify Continuous Probability Distributions with KNIME (implementation) https://www.knime.com/blog/identify-continuous-probability-distribution

Continuous Probability Distribution This workflow takes in data where numeric columns are chosen to determine which continuous probability distribution the data follows. The component returns the five best fit distributions, probability plots and descriptive stats for the selected column(s).
Company profit per year
CSV Reader
Multiple columns
Continuous Probability Distribution
Multiple columns
Continuous Probability Distribution
Gender, height, weight dataset
CSV Reader

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Swetha Kannan
Created at: 2022-06-10
On NodePit since: 2026-09-14
Last update: 2026-09-14
Created with KNIME version: v5.12.0
Tags: Continuous probability distributionNormal distributionStatisticst-distributionUniform distribution

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