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Personalized and Reliable Predictive Models for Healthcare (의료 데이터 기반 신뢰 가능한 개인화된 예측(진단) 모델)

License: Apache License 2.0

Makefile 0.21% Python 16.88% Jupyter Notebook 82.86% Shell 0.02% Dockerfile 0.03%

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mixed-effect-composite-rnn-gaussian-process's Issues

Can the model perform regression tasks?

I tried to apply this model to a regression problem, but the y_pred obtained in the model.predicT_y (X) step is always a value greater than 0 and less than 1. Do I need to normalize the target variable Y?

GPflow Version

Hello,
This is a very interesting implementation. Can you please let me know which version of GPflow you used. I got the following error:

(py3) ➜  Mixed-Effect-Composite-RNN-Gaussian-Process-master python run_mecgp.py
Traceback (most recent call last):
  File "run_mecgp.py", line 12, in <module>
    import GPflow.gpflow as gpflow
  File "/Users/mohammad/workspace/research-2/Mixed-Effect-Composite-RNN-Gaussian-Process-master/GPflow/gpflow/__init__.py", line 19, in <module>
    from . import (likelihoods, kernels, ekernels, param,
  File "/Users/mohammad/workspace/research-2/Mixed-Effect-Composite-RNN-Gaussian-Process-master/GPflow/gpflow/model.py", line 19, in <module>
    from .mean_functions import Zero
  File "/Users/mohammad/workspace/research-2/Mixed-Effect-Composite-RNN-Gaussian-Process-master/GPflow/gpflow/mean_functions.py", line 21, in <module>
    from layers import affine_relu_forward, affine_forward
ModuleNotFoundError: No module named 'layers'

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