hello,the Python version of causally-Regularized-learning about causally-regularized-learning HOT 8 OPEN

@xiaowei-ui Working on it, python implementation will be released this fall.

from causally-regularized-learning.

@ xiaowei-ui正在研究它，今年秋天将发布python实现。
that's ok,thank you!

from causally-regularized-learning.

@ xiaowei-ui正在研究它，今年秋天将发布python实现。
that's ok,thank you!

@xiaowei-ui Working on it, python implementation will be released this fall.

excuse me，how is the prediction matrix I generated by the feature matrix X? The demo is through the ’double‘ function, what function should be used in the neural network?

from causally-regularized-learning.

@ xiaowei-ui正在研究它，今年秋天将发布python实现。
that's ok,thank you!

@xiaowei-ui Working on it, python implementation will be released this fall.

excuse me，how is the prediction matrix I generated by the feature matrix X? The demo is through the ’double‘ function, what function should be used in the neural network?

Which matrix I do you mean? There is no I in demo...

from causally-regularized-learning.

@ xiaowei-ui正在研究它，今年秋天将发布python实现。
that's ok,thank you!

@xiaowei-ui Working on it, python implementation will be released this fall.

excuse me，how is the prediction matrix I generated by the feature matrix X? The demo is through the ’double‘ function, what function should be used in the neural network?

Which matrix I do you mean? There is no I in demo...

the sevnth line code of the balance_cost function,

from causally-regularized-learning.

@xiaowei-ui It is actually the indicator of whether a sample receive treatment, for binary feature, I = X_j > 0 (double only act as type conversion). We do not discuss continuous feature in our scope, but you can refer to causal inference literature for more information.

from causally-regularized-learning.

@xiaowei-ui It is actually the indicator of whether a sample receive treatment, for binary feature, I = X_j > 0 (double only act as type conversion). We do not discuss continuous feature in our scope, but you can refer to causal inference literature for more information.

First of all, thanks for your reply,dear author,then if I use the pretrain model to extract features, what should I do with the features specificly to get the Xtrain(n*p) form in the paper, and how to handle the features to fit the input X matrix in the code?

from causally-regularized-learning.

@xiaowei-ui perform binarization on X would be enough i think

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