Working on #2963 , I see two warnings generated when building the R package using MSVC.

C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\MSBuild\Microsoft\VC\v160\Microsoft.CppBuild.targets(467,5):
warning MSB8029: The Intermediate directory or Output directory cannot reside under the Temporary directory as it could lead to issues with incremental build.

config.cpp
C:\

I don't see any documentation on how to sort the variables in the plot. I don't want them sorted by shap value but in the original order, since i'm studying the behaviour of a Wave and I want to see a multiclass distribution of shap values over time

Currently they appear as

t=24
t=32
t=1
....

I want them to appear as
t=1
t=2
t=3
t=4
...

Is it possible?

This is an awesome library, thanks @ddbourgin!!

Users might not know the best way to install this package and try it out. (I didn't, so I eventually just copied the source files.)
Neither the readme nor readthedocs have install instructions.

I couldn't find it on PyPi or Anaconda, and there doesn't appear to be a pyproject.toml, setup.cfg, setup.py, or conda recipe.

Moreover, the t

Hi,
I'm new to tpot but I got this error. I understand that score function can take strings, but I got the following error when using TPOTClassifier.

---

ValueError Traceback (most recent call last)
in
----> 1 tpot.score(X_test, y_test)

~/miniconda3/envs/ml

This class could be used instead of cd file https://catboost.ai/docs/concepts/input-data_column-descfile.html when creating Pool from filez. The class should have init function, methods load and save, and Pool init method should be able to use object of this class instead of cd file during initialization.

Would you write some docstrings for the models? Docstrings and explanations for the model parameters would make it easier to understand and use them.

I run this code

import os
os.environ['is_test_suite']="True" # this is writen due to bug for multiprocessing and pickling I issued. #426 
from auto_ml import Predictor
from auto_ml.utils import get_boston_dataset
from auto_ml.utils_models import load_ml_model

# Load data
df_train, df_test = get_boston_dataset()

# Tell auto_ml which column is 'output'
# Also note columns t

Doxygen headers have been added for all files, but function and class documentation needs to be added (starting with drishti public API).

TODO: The standard library style namespace macros (which prevent IDE indentation) are currently confusing doxygen. This needs to be fixed.

How can I configure it for my native language?& if I want to test yours, how would I start the training & test the model?