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simulate categorical features for tabular data for binary classification

task is not so simple as seems to be

you should be very good in Mathematical Statistics , especially in random data simulations

you define dependency by correlation matrix , as parameter

do not forget include dependency between features and features and target

simulate data by yourself with predefined patterns,

for example

data 1 million rows for example 20 categorical features each feature has unique 570 categorical values

then in average

140 observations for one unique value

140~ = 100000 / 570

for example these may be not good:

[login to view URL]

[login to view URL]

**** MAIN DIFFICULTY IS SMALL NUMBER OF OBSERVATIONS FOR EACH UNIQUE VALUE and patterns in data ***

it is much more complicated than

[login to view URL]

[login to view URL]

since predefined patterns are needed

key part is dependency

1

between features

2

features and target

Compétences : Mathématiques, Python, Machine Learning (ML), Statistiques

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Concernant l'employeur :
( 5 commentaires ) Toronto, Canada

Nº du projet : #29446152

19 freelances font une offre moyenne de 163 $ pour ce travail

schoudhary1553

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(92 Commentaires)
6.9
RushService

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5.6
TheLKteam

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5.1
supreetsingh2020

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ranjanisi

Hello, I am PhD student working in ML and CV. I think I will be able to do this project in categorical random data simulations. Please give us more details regarding this project. Thank you.

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