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mall_​customer(PCA+cluster discovery)

Numero di cluster ottimale per k-Means col metodo di Elbow
dataset: mall_customerProprietà: PacktPublishinghttps://github.com/PacktPublishing/Data-Science-for-Marketing-Analytics-Second-Edition/blob/master/Chapter03/Datasets/Mall_Customers.csvLicenza: MIT License Mall_customerNormalizzazioneClusteringde-normalizzazionedispersione(calcolo cluster)medieClusterriduzionedella dimensionalitàEliminocolonne nondi interesseElbowkLoop da 1 a 10ShowElbow CSV Reader Normalizer k-Means Denormalizer Scatter Plot Color Manager Bar Chart PCA Column Filter Calculate sum ofsquared errors Java Edit Variable Find Elbow Counting Loop Start Line Plot Loop End Variable toTable Column dataset: mall_customerProprietà: PacktPublishinghttps://github.com/PacktPublishing/Data-Science-for-Marketing-Analytics-Second-Edition/blob/master/Chapter03/Datasets/Mall_Customers.csvLicenza: MIT License Mall_customerNormalizzazioneClusteringde-normalizzazionedispersione(calcolo cluster)medieClusterriduzionedella dimensionalitàEliminocolonne nondi interesseElbowkLoop da 1 a 10ShowElbow CSV Reader Normalizer k-Means Denormalizer Scatter Plot Color Manager Bar Chart PCA Column Filter Calculate sum ofsquared errors Java Edit Variable Find Elbow Counting Loop Start Line Plot Loop End Variable toTable Column

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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: falai
Created at: 2022-08-19
On NodePit since: 2022-09-05
Last update: 2024-12-17
Created with KNIME version: v4.6.1
Tags: Elbowk-Means

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