HiExample_DB.xlsx (10.0 KB) ,
I have a university student database. Usually, each student has 3 or 4 school grades from 19 different school courses. Therefore each student has 19-3(4)=16(15) missing values. There are names of university study programs also. I need to predict for school pupils:
- admission probability for each study program
- how “typical” student he will be in each study program.
School pupils usually have all grades.
values of each grade from 1 to 10. there is a positive correlation between school grades.
I’m trying to use Anomaly Detection algorithm e.g. EXAMPLES/50_Applications/39_Fraud_Detection/Keras_Autoencoder_for_Fraud_Detection_Training
But node Keras Network Learner doesn’t work with missing values.
How to replace (restore) the missing value? or maybe there is another way to predict admission likelihood?