openxaiproject / mixed-effect-composite-rnn-gaussian-process Goto Github PK
View Code? Open in Web Editor NEWPersonalized and Reliable Predictive Models for Healthcare (의료 데이터 기반 신뢰 가능한 개인화된 예측(진단) 모델)
License: Apache License 2.0
Personalized and Reliable Predictive Models for Healthcare (의료 데이터 기반 신뢰 가능한 개인화된 예측(진단) 모델)
License: Apache License 2.0
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?
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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