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»¨éÂçÿÿHƒìHƒÄÃintlongan integer is required__pyx_capi__name '%.200s' is not defined__cinit__sklearn/tree/_criterion.c%s (%s:%d)sklearn/tree/_criterion.pyxexactlyend'char''signed char''unsigned char''short''unsigned short''int''unsigned int''long''unsigned long''long long''unsigned long long''float''double''long double'a structPython objecta pointera stringunparseable format string'complex long double''complex double''complex float'tupleExpected %.16s, got %.200sMissing type object__init__.pxdnumpy._util_dtypestringn_classesnumpy.ndarray.__getbuffer__buffer dtypetype.pxdsklearn/tree/_utils.pxd%d.%d%s__builtin____builtins____name__RegressionCriterionFriedmanMSEnumpyflatiterbroadcastufuncStacksklearn.tree._utilsPriorityHeapsizet_ptr_to_ndarraydouble (double)log__pyx_fuse_0safe_realloc__pyx_fuse_1safe_realloc__pyx_fuse_2safe_reallocnumpy.core.multiarray_ARRAY_API_ARRAY_API not found_ARRAY_API is NULL pointerinit sklearn.tree._criterionClassificationCriterionEntropysklearn.tree._criterion.MSE__reduce__sklearn.tree._criterion.Gini__getstate____setstate__SIZE_t__%.4s__ returned non-%.4s (type %.200s)value too large to convert to intinvalid vtable found for imported type%.200s.%.200s is not a type object%s.%s size changed, may indicate binary incompatibility%.200s.%.200s has the wrong size, try recompiling%.200s does not export expected C function %.200sC function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)%.200s() got an unexpected keyword argument '%.200s'%s() got multiple values for keyword argument '%s'%.200s() keywords must be strings while calling a Python objectNULL result without error in PyObject_Callraise: arg 3 must be a traceback or Noneinstance exception may not have a separate valueraise: exception class must be a subclass of BaseExceptionsklearn.tree._criterion.ClassificationCriterion.__reduce__sklearn.tree._criterion.Criterion.__getstate__sklearn.tree._criterion.RegressionCriterion.__cinit__%.200s() takes %.8s %zd positional argument%.1s (%zd given)Buffer dtype mismatch, expected %s%s%s but got %sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dUnexpected format string character: '%c'Python does not define a standard format string size for long double ('g')..Buffer dtype mismatch; next field is at offset %zd but %zd expectedBig-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringDoes not understand character buffer dtype format string ('%c')Expected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'sklearn.tree._criterion.RegressionCriterion.__reduce__'NoneType' object is not iterable'NoneType' object is not subscriptabletoo many values to unpack (expected %zd)need more than %zd value%.1s to unpackCannot convert %.200s to %.200sArgument '%.200s' has incorrect type (expected %.200s, got %.200s)sklearn.tree._criterion.ClassificationCriterion.__cinit__'%.200s' does not have the buffer interfaceBuffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)compiletime version %s of module '%.100s' does not match runtime version %sPyArrayObject *(__pyx_t_7sklearn_4tree_6_utils_SIZE_t *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t)__pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t)__pyx_t_7sklearn_4tree_6_utils_SIZE_t *(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t)unsigned char *(unsigned char **, size_t)numpy.core.multiarray failed to import_ARRAY_API is not PyCObject objectmodule compiled against ABI version %x but this version of numpy is %xmodule compiled against API version %x but this version of numpy is %xFATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtimesklearn.tree._criterion.FriedmanMSEMean squared error impurity criterion with improvement score by Friedman

    Uses the formula (35) in Friedmans original Gradient Boosting paper:

        diff = mean_left - mean_right
        improvement = n_left * n_right * diff^2 / (n_left + n_right)
    Mean squared error impurity criterion.

        MSE = var_left + var_right
    sklearn.tree._criterion.RegressionCriterionAbstract regression criterion.

    This handles cases where the target is a continuous value, and is
    evaluated by computing the variance of the target values left and right
    of the split point. The computation takes linear time with `n_samples`
    by using ::

        var = \sum_i^n (y_i - y_bar) ** 2
            = (\sum_i^n y_i ** 2) - n_samples * y_bar ** 2
    Gini Index impurity criterion.

    This handles cases where the target is a classification taking values
    0, 1, ... K-2, K-1. If node m represents a region Rm with Nm observations,
    then let

        count_k = 1/ Nm \sum_{x_i in Rm} I(yi = k)

    be the proportion of class k observations in node m.

    The Gini Index is then defined as:

        index = \sum_{k=0}^{K-1} count_k (1 - count_k)
              = 1 - \sum_{k=0}^{K-1} count_k ** 2
    sklearn.tree._criterion.EntropyCross Entropy impurity criterion.

    This handles cases where the target is a classification taking values
    0, 1, ... K-2, K-1. If node m represents a region Rm with Nm observations,
    then let

        count_k = 1 / Nm \sum_{x_i in Rm} I(yi = k)

    be the proportion of class k observations in node m.

    The cross-entropy is then defined as

        cross-entropy = -\sum_{k=0}^{K-1} count_k log(count_k)
    sklearn.tree._criterion.ClassificationCriterionAbstract criterion for classification.sklearn.tree._criterion.CriterionInterface for impurity criteria.

    This object stores methods on how to calculate how good a split is using
    different metrics.
    
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sklearn/tree/usr/include/x86_64-linux-gnu/bits/home/travis/virtualenv/python2.7.11/lib/python2.7/site-packages/numpy/core/include/numpy/usr/lib/gcc/x86_64-linux-gnu/4.8/include/usr/include/opt/python/2.7.11/include/python2.7_criterion.c
string3.h__multiarray_api.hstddef.htypes.hstdio.hlibio.hunistd.hpyport.hobject.hmethodobject.hdescrobject.hintobject.hlongobject.hstringobject.htupleobject.hclassobject.hpycapsule.hframeobject.hpystate.hcode.hnpy_common.hndarraytypes.h__ufunc_api.hunicodeobject.hboolobject.hbytearrayobject.hcobject.htraceback.hpyerrors.hceval.habstract.hstdlib.hdictobject.himport.hwarnings.hmoduleobject.hpymem.hpythonrun.hlistobject.hmodsupport.h	À1‹

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