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```
best=self.invokeScoring(blackBoxIteration, pb, context)
File "\nick\projects\uniopt\UniOpt\backends\pyshac.py", line 107, in invokeScoring
shac.fit(pyshacScore, skip_cv_checks=self.sk…
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Hi,
We just finished a nasty but eventually successful 9-month search for a high-dimension, very non-linear, chock full of outliers, real world regression modeling problem. While we have a brea…
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HI
ther's a problem when You try to rerun the optimizer with 'exactly' the same
hyperparameters's range of values;
for example, if I declare:
'max_depth'=Integer(2, 15)
and any other Real hy…
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I build xgboost from source and installed the module all successfully but cannot import…
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Testing the XGB with params, I put incorrectly the objective param
objective="reg:logitic"
The result was a run with an output of same predict for each case. This should check if the parameter was p…
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Hi dear Sir,
I've spent a lot of time trying to run the code, but without success. I always get mistakes. In fact:
The first one was about downsample. To solve it, i uploaded the lasagne package l…
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I'm trying to run spark-sklearns GridSearch on an HDInsight Cluster from Azure. Here is a Code Snippet:
```
model = KerasRegressor(build_fn=build_model, verbose=0)
kf = KFold(n_…
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Sorry, if this is the wrong place to post this. My code:
```
from sklearn import datasets, linear_model, cross_validation, grid_search
import numpy as np
digits = datasets.load_digits()
x = digits.da…
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Bug, había colocado como método cv en vez de timeslices
CAmbiar esto
my.train.control
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It seems like they might have made some changes to their cross_validation classes, but this should be looked into more carefully. Stick with 16.1 until this is resolved.
## Here is the error message …