Closed
Description
Subsequent to #12522 it seems I get the following test failure when running on my own machine. @NicolasHug is this level of imprecision surprising?
____________________________________ [doctest] sklearn.preprocessing.data.PowerTransformer ____________________________________
2521
2522 Examples
2523 --------
2524 >>> import numpy as np
2525 >>> from sklearn.preprocessing import PowerTransformer
2526 >>> pt = PowerTransformer()
2527 >>> data = [[1, 2], [3, 2], [4, 5]]
2528 >>> print(pt.fit(data))
2529 PowerTransformer(copy=True, method='yeo-johnson', standardize=True)
2530 >>> print(pt.lambdas_)
Expected:
[ 1.38668178 -3.10053309]
Got:
[ 1.38668178 -3.10053332]
show_versions
System:
python: 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:52:12) [GCC 4.2.1 Compatible Apple LLVM 4.2 (clang-425.0.28)]
machine: Darwin-17.7.0-x86_64-i386-64bit
executable: /Users/joel/anaconda3/envs/scipy3k/bin/python
BLAS:
cblas_libs: mkl_rt, pthread
lib_dirs: /Users/joel/anaconda3/envs/scipy3k/lib
macros: SCIPY_MKL_H=None, HAVE_CBLAS=None
Python deps:
pandas: 0.23.4
pip: 18.0
sklearn: 0.20.1 # at 19c3008
setuptools: 37.0.0
Cython: 0.28.5
scipy: 1.0.0
numpy: 1.14.1