CTGAN

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Gaussian approximation of continuous variables really clear in non-gaussian/non-multimodal data

5

In columns where the continuous data is distributed in a really non-gaussian approximable way (e.g. Dates that increase in frequency) and follow a line are not well approximated with the...

Baukebrenninkmeijer

### Environment details If you are already running CTGAN, please indicate the following details about the environment in which you are running it: * CTGAN version: * Python version: *...

ItsyPetkov

Hi! Has anyone already worked out a way to use pruning or another way of early stopping with CTGAN? I guess one has to edit the code of CTGAN itself...

jeiglsperger

DataTransformer init parameters

4

This PR solve issue #7, it allows two things: 1. ability to fit gaussian mixtures on a subsample (help to scale with big datasets while losing only little accuracy) 2....

FlorentRamb

Synthetic data has 25%-50% repeated values

1

### Environment details If you are already running CTGAN, please indicate the following details about the environment in which you are running it: * CTGAN version: 0.5.1 * Python version:...

nejadhav

Hi Team, Is there an SDV version that works with ctgan 0.4.3 and torch 1.12.1+cu102? I am asking this because we want an SDV version that can work along with...

dsrishti

This PR fixes issue #246.

AndresAlgaba

### Environment Details Please indicate the following details about the environment in which you found the bug: * CTGAN version: master branch * Python version: 3.9 * Operating System: Windows...

AndresAlgaba

Fixed small typos

1

- Added dash (-) to change from "Deep Learning based" to "Deep Learning-based". - Added "C" to change from "TGAN" to "CTGAN".

mahmadza

ValueError: mismatch of shapes when sampling data for compas dataset

1

### Environment Details Please indicate the following details about the environment in which you found the bug: * CTGAN version: 0.8.0 * Python version: 3.9.6 * Pandas version: 2.0.3 *...

bronval