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simulate tabular data with categorical features for binary classification

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:

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

it is much more complicated than

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since predefined patterns are needed

key part is dependency

1

between features

2

features and target

Skills: Python, Machine Learning (ML), Mathematics, Simulation, Statistical Analysis

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About the Employer:
( 5 reviews ) Toronto, Canada

Project ID: #29370152

9 freelancers are bidding on average $147 for this job

ibrahimanjum330

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