I'm training a neural network to predict the number of fan growth of a Facebook page based on the no of posts, the category of post(video, link,status etc) and number of shares ,like & comments for each post. So, there is a single label against multiple instances as label(fan_growth) is being calculated for each day(not for each post):
So If i use one hot encoding for categorical data:
here date,day,link,video,status,reactions,comments and shares are features, while fan_growth is label. How can I use single label against more than 1 instance? As using '100' again all 1st 3 instances would not be correct.