documentation

README.md

@@ -12,7 +12,8 @@ This package is designed to generate synthetic data from a dataset from an origi
 ## Usage
 
 After installing the easiest way to get started is as follows (using pandas). The process is as follows:
-1. Train the GAN on the original/raw dataset
+
+**Train the GAN on the original/raw dataset**
 
 
     import pandas as pd
@@ -27,7 +28,7 @@ data.maker.train(context=context,data=df,column=column,id=id,logs='logs')
 The trainer will store the data on disk (for now) in a structured folder that will hold training models that will be used to generate the synthetic data.
 
 
-2. Generate a candidate dataset from the learnt features
+**Generate a candidate dataset from the learned features**
 
 
         import pandas as pd
@@ -46,11 +47,14 @@ 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]
+        
 - Not advised on continuous values
 
         GANS work well on discrete values and thus are not advised to be used.
         e.g:measurements (height, blood pressure, ...)
+- For now will only perform on a single feature.
 
 ## Credits :