From caab8800dd09bfe54314dd60e1c83e0abdeb110a Mon Sep 17 00:00:00 2001 From: Steve Nyemba Date: Thu, 12 Dec 2019 12:15:05 -0600 Subject: [PATCH] documentation/layout --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 48b01aa..9589ddd 100644 --- a/README.md +++ b/README.md @@ -33,7 +33,7 @@ After installing the easiest way to get started is as follows (using pandas). Th df = data.maker.generate(logs='logs') df.head() - + ## Limitations --- @@ -42,8 +42,10 @@ GANS will generate data assuming the original data has all the value space neede - No new data will be created - Assuming we have a dataset with an gender attribute with values [M,F]. The synthetic data will not be able to generate genders outside [M,F] + Assuming we have a dataset with an gender attribute with values [M,F]. + The synthetic data will not be able to generate genders outside [M,F] - Not advised on continuous values - GANS work well on discrete values and thus are not advised to be used to synthesize things like measurements (height, blood pressure, ...) + GANS work well on discrete values and thus are not advised to be used. + e.g:measurements (height, blood pressure, ...)