Customer Segmentation using K-prototypes in Python

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Customer Segmentation using K-prototypes / K-means in Python.
In this tutorial, we implement the K-prototype algorithm to segment customers.

AI Decoder

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aidecoder

is it okey to apply PCA on labeled categorical data?

reference:
[...]
#concatenate the data
Data=pd.concat([df_cat, df_num], axis=1)
[...]
d_f= pca.fit_transform(Data)

SlashSung

Nice video. Can you please fix the audio as its too low.

prasannabb

When I try to KneeLocator method, it gives me an error : ValueError: x and y arrays must be equal in length along interpolation axis.
Can you help, how can I handle this?

fxfnfwn

Hey, thank you for the illustration. i'm trying the code but at the step of the clustering i faced a problem that i couldn't solve, the below error appeared, how can i solve it ?
ValueError: need at most 63 handles, got a sequence of length 65

hadyshaaban

How to find centroid using k prototypes ?

aldisetiadi

Hi, well explained!
My question: why you haven't standardized the data before applying k-prototype?

tusharnaikwade

Whao! Nice Tutorial! Is there now a way to detect Outliers of each cluster?

piet

Why do you need to encode the categorical variables with numeric values? In another video i saw, the categorical variables can be used directly without being encoded before.
Thanks

andychaurusno

How will you validate or evaluate the cluster?

gopirm

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