Hi Shojiro,
This might not be the most elegant and efficient way but it worked for what
I wanted to do. I changed my apply function as below:
allDescp=[name[0] for name in Descriptors._descList]
for name in allDescp:
temp=MoleculeDescriptors.MolecularDescriptorCalculator([name])
hi Shojiro,
Thanks for your response but print
(np.argsort(rfregress.feature_importances_)[::-1]) returns the row indices
but what I want is the column names so it can give me information which
features are important.
On Mon, Aug 20, 2018 at 9:31 PM Shojiro Shibayama
wrote:
> Dear Ali,
>
>
Dear Ali,
Please run first the following code, which may help you:
```python
import numpy as np
np.argsort(rfregress.feature_importances_)[::-1]
```
The `argsort` will return the indexes of the important features in
ascending order and [::-1] reverses the order.
The indexes for feature
Hello rdkit,
This might be trivial but I am beginner and don't know how to do it.
I am building a simple model to predict target property. I have pandas
dataframe (df) whose columns are 'SMILES' and 'Target'.
#calculating the descriptors as below:
llDescp=[name[0] for name in
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