gradient-boosting
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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.
When running
from interpret import show
from interpret.perf import ROC
blackbox_perf = ROC(blackbox_model.predict_proba).explain_perf(X_test, y_test, name='Blackbox')
show(blackbox_perf)
I have the following error
RuntimeError: Could not find open port.
Consider calling interpret.set_show_addr(("127.0.0.1", 7001)) first..
Even calling the set_show_addr, I
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-
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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.
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How can I configure it for my native language?& if I want to test yours, how would I start the training & test the model?
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One unit test in the R package is currently broken. Steps to reproduce on Mac
This results in the following error at the ends of the logs