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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

Skills: Mathematics, Python, Machine Learning (ML), Statistics

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About the Employer:
( 5 reviews ) Toronto, Canada

Project ID: #29446152

19 freelancers are bidding on average $163 for this job

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