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- Find the best possible split of a node. For a given node, a split is
  characterized by a feature and a bin.
- Apply a split to a node, i.e. split the indices of the samples at the node
  into the newly created left and right childs.
Pure data class to store information about a potential split.

    Parameters
    ----------
    gain : float
        The gain of the split.
    feature_idx : int
        The index of the feature to be split.
    bin_idx : int
        The index of the bin on which the split is made.
    missing_go_to_left : bool
        Whether missing values should go to the left child.
    sum_gradient_left : float
        The sum of the gradients of all the samples in the left child.
    sum_hessian_left : float
        The sum of the hessians of all the samples in the left child.
    sum_gradient_right : float
        The sum of the gradients of all the samples in the right child.
    sum_hessian_right : float
        The sum of the hessians of all the samples in the right child.
    n_samples_left : int, default=0
        The number of samples in the left child.
    n_samples_right : int
        The number of samples in the right child.
    Out of bounds on buffer access (axis %d)Non-native byte order not supportedInvalid mode, expected 'c' or 'fortran', got %sIndirect dimensions not supportedIncompatible checksums (%s vs 0xb068931 = (name))Incompatible checksums (%s vs 0x6f78f92 = (X_binned, has_missing_values, hessians_are_constant, l2_regularization, left_indices_buffer, min_gain_to_split, min_hessian_to_split, min_samples_leaf, missing_values_bin_idx, monotonic_cst, n_bins_non_missing, n_features, partition, right_indices_buffer))Format string allocated too short, see comment in numpy.pxdEmpty shape tuple for cython.arrayCannot create writable memory view from read-only memoryviewCannot assign to read-only memoryviewCan only create a buffer that is contiguous in memory.Buffer view does not expose stridesunknown dtype code in numpy.pxd (%d)sklearn.ensemble._hist_gradient_boosting.splittingnumpy.core.multiarray failed to import<strided and direct or indirect>unable to allocate array data.itemsize <= 0 for cython.arrayInvalid shape in axis %d: %d.Cannot index with type '%s'<contiguous and indirect><MemoryView of %r at 0x%x>missing_values_bin_idx<MemoryView of %r object>__pyx_unpickle_Splitterhessians_are_constant<contiguous and direct><strided and indirect>min_hessian_to_splitsum_gradient_right<strided and direct>n_bins_non_missingmissing_go_to_lefthas_missing_valuescline_in_tracebacksum_hessian_rightsum_gradient_left__pyx_unpickle_Enummin_gain_to_splitl2_regularizationsum_hessian_leftmin_samples_leafSplitInfo.__init____setstate_cython____pyx_PickleErrorn_samples_rightdtype_is_objectallocate_bufferView.MemoryViewHISTOGRAM_DTYPEsample_indicesn_samples_leftsum_gradients__reduce_cython____pyx_getbuffermonotonic_cstsum_hessianssum_gradientstringsource__pyx_checksumRuntimeErrorvalue_rightupper_boundsum_hessianlower_boundfeature_idxPickleErrorMemoryErrorImportErrorvalue_leftsplit_info__pyx_vtable____pyx_resulthistogramsempty_likeValueErrorIndexError__reduce_ex____pyx_staten_samples__metaclass__enumerateTypeErrorSplitInfo__setstate____qualname____pyx_typeitemsize__getstate__X_binnedSplitterEllipsis__prepare__memviewfortranbin_idxupdateunpackuint32struct__reduce__pickle__name____module____import__formatencodecommonarangezerosvaluestartshaperangenumpyint32flagserroremptydtype__class__ASCII__test__stopstepsizeselfpackndimnamemode__main____init__gainfull__dict__baseobj__new____doc__npidcOBuffer dtype mismatch, expected %s%s%s but got %sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'memviewslice is already initialized!%.200s() takes no arguments (%zd given)%.200s() takes exactly one argument (%zd given)Bad call flags in __Pyx_CyFunction_Call. METH_OLDARGS is no longer supported!%.200s() takes no keyword arguments%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectUnable to initialize pickling for %s__annotations__ must be set to a dict object__kwdefaults__ must be set to a dict object__defaults__ must be set to a tuple objectfunction's dictionary may not be deletedsetting function's dictionary to a non-dict__qualname__ must be set to a string object__name__ must be set to a string objectDoes not understand character buffer dtype format string ('%c')Cannot convert %.200s to %.200ssklearn/ensemble/_hist_gradient_boosting/splitting.cView.MemoryView.memoryview.__str__View.MemoryView.memoryview.size.__get__View.MemoryView.memoryview.nbytes.__get__View.MemoryView.memoryview.itemsize.__get__View.MemoryView.memoryview.ndim.__get__View.MemoryView.memoryview.suboffsets.__get__View.MemoryView.memoryview.shape.__get__View.MemoryView.memoryview.assign_item_from_objectView.MemoryView._memoryviewslice.assign_item_from_objectView.MemoryView.memoryview.setitem_indexedView.MemoryView.array.memview.__get__View.MemoryView.array.__getattr__View.MemoryView.array.__getitem__View.MemoryView.array.__setitem__Subscript deletion not supported by %.200ssklearn/ensemble/_hist_gradient_boosting/splitting.pyxsklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_gain_to_split.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_samples_leaf.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_hessian_to_split.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.l2_regularization.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.hessians_are_constant.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.missing_values_bin_idx.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.n_features.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.l2_regularization.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_hessian_to_split.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_gain_to_split.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter._find_best_bin_to_split_right_to_left__int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.__%.4s__ returned non-%.4s (type %.200s)Unexpected format string character: '%c'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dPython 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 stringExpected 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 ')'%s() got multiple values for keyword argument '%U'%.200s() keywords must be strings%s() got an unexpected keyword argument '%U'%.200s() takes %.8s %zd positional argument%.1s (%zd given)sklearn.ensemble._hist_gradient_boosting.splitting.compute_node_valuesklearn.ensemble._hist_gradient_boosting.splitting.SplitInfo.__init__Acquisition count is %d (line %d)calling %R should have returned an instance of BaseException, not %Rraise: exception class must be a subclass of BaseExceptionView.MemoryView.array.__reduce_cython__View.MemoryView.array.__setstate_cython__View.MemoryView.memoryview.convert_item_to_objectView.MemoryView._memoryviewslice.convert_item_to_objectView.MemoryView.memoryview.__reduce_cython__View.MemoryView.memoryview.__setstate_cython__View.MemoryView.memoryview.strides.__get__View.MemoryView._memoryviewslice.__reduce_cython__View.MemoryView._memoryviewslice.__setstate_cython__PyObject_GetBuffer: view==NULL argument is obsoleteView.MemoryView.array.__getbuffer__View.MemoryView.memoryview.__getbuffer__View.MemoryView.array.get_memviewView.MemoryView.memoryview_cwrapperBuffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zu byte%s) does not match size of '%s' (%zu byte%s)Buffer is not indirectly contiguous in dimension %d.Buffer and memoryview are not contiguous in the same dimension.C-contiguous buffer is not contiguous in dimension %dC-contiguous buffer is not indirect in dimension %dBuffer exposes suboffsets but no stridesBuffer not compatible with direct access in dimension %d.Buffer is not indirectly accessible in dimension %d.Buffer not fortran contiguous.View.MemoryView.memoryview.is_slicesklearn.ensemble._hist_gradient_boosting.splitting.Splitter._find_best_bin_to_split_left_to_rightView.MemoryView.memoryview.__repr__View.MemoryView.Enum.__reduce_cython__c-string too long to convert to PythonStep may not be zero (axis %d)All dimensions preceding dimension %d must be indexed and not slicedView.MemoryView.slice_memviewsliceView.MemoryView.memoryview_fromsliceView.MemoryView.memoryview_copy_from_slicesklearn.ensemble._hist_gradient_boosting.splitting.Splitter.right_indices_buffer.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.left_indices_buffer.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.partition.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.monotonic_cst.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.has_missing_values.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.n_bins_non_missing.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.X_binned.__get__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.__reduce_cython__value too large to convert to intView.MemoryView.get_slice_from_memviewView.MemoryView.memoryview.is_f_contigView.MemoryView.memoryview.is_c_contigView.MemoryView.assert_direct_dimensionsView.MemoryView.memoryview.setitem_slice_assign_scalarvalue too large to convert to unsigned charcan't convert negative value to unsigned charsklearn.ensemble._hist_gradient_boosting.splitting.Splitter.missing_values_bin_idx.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.hessians_are_constant.__set__value too large to convert to unsigned intcan't convert negative value to unsigned intsklearn.ensemble._hist_gradient_boosting.splitting.Splitter.min_samples_leaf.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.n_features.__set__value too large to convert to npy_uint8can't convert negative value to npy_uint8sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.monotonic_cst.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.left_indices_buffer.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.right_indices_buffer.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.has_missing_values.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.X_binned.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.n_bins_non_missing.__set__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.partition.__set__'NoneType' object is not subscriptablehasattr(): attribute name must be stringView.MemoryView.__pyx_unpickle_Enum__set_stateView.MemoryView.Enum.__setstate_cython__Cannot transpose memoryview with indirect dimensionsView.MemoryView.transpose_memsliceView.MemoryView.memoryview_copyView.MemoryView.memoryview.T.__get__View.MemoryView.copy_data_to_tempView.MemoryView.memoryview_copy_contentsCannot copy memoryview slice with indirect dimensions (axis %d)View.MemoryView.array_cwrapperView.MemoryView.memoryview.copy_fortranView.MemoryView.memoryview.copyView.MemoryView.__pyx_unpickle_Enuminteger division or modulo by zerovalue too large to perform divisionView.MemoryView.pybuffer_indexView.MemoryView.memoryview.get_item_pointerView.MemoryView.memoryview.__cinit__local variable '%s' referenced before assignmenttoo many values to unpack (expected %zd)need more than %zd value%.1s to unpack'NoneType' object is not iterableView.MemoryView.memoryview.__setitem__View.MemoryView.memoryview.__getitem__sklearn.ensemble._hist_gradient_boosting.splitting.Splitter.split_indicessklearn.ensemble._hist_gradient_boosting.splitting.Splitter.find_node_splitsklearn.ensemble._hist_gradient_boosting.splitting.Splitter.__init__View.MemoryView.memoryview.setitem_slice_assignmentView.MemoryView.array.__cinit__Argument '%.200s' must not be Noneobject of type 'NoneType' has no len()expected bytes, NoneType foundArgument '%.200s' has incorrect type (expected %.200s, got %.200s)sklearn.ensemble._hist_gradient_boosting.splitting.__pyx_unpickle_Splitter__set_statesklearn.ensemble._hist_gradient_boosting.splitting.__pyx_unpickle_Splittersklearn.ensemble._hist_gradient_boosting.splitting.Splitter.__setstate_cython__sklearn.ensemble._hist_gradient_boosting.splittingcompiletime version %s of module '%.100s' does not match runtime version %sShared Cython type %.200s is not a type objectShared Cython type %.200s has the wrong size, try recompiling_ARRAY_API is not PyCapsule objectmodule compiled against ABI version 0x%x but this version of numpy is 0x%xmodule compiled against API version 0x%x but this version of numpy is 0x%xFATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtimeinit sklearn.ensemble._hist_gradient_boosting.splittingsklearn.ensemble._hist_gradient_boosting.splitting._memoryviewsliceInternal class for passing memoryview slices to Pythonsklearn.ensemble._hist_gradient_boosting.splitting.memoryviewsklearn.ensemble._hist_gradient_boosting.splitting.Enumsklearn.ensemble._hist_gradient_boosting.splitting.arraysklearn.ensemble._hist_gradient_boosting.splitting.SplitterSplitter used to find the best possible split at each node.

    A split (see SplitInfo) is characterized by a feature and a bin.

    The Splitter is also responsible for partitioning the samples among the
    leaves of the tree (see split_indices() and the partition attribute).

    Parameters
    ----------
    X_binned : ndarray of int, shape (n_samples, n_features)
        The binned input samples. Must be Fortran-aligned.
    n_bins_non_missing : ndarray, shape (n_features,)
        For each feature, gives the number of bins actually used for
        non-missing values.
    missing_values_bin_idx : uint8
        Index of the bin that is used for missing values. This is the index of
        the last bin and is always equal to max_bins (as passed to the GBDT
        classes), or equivalently to n_bins - 1.
    has_missing_values : ndarray, shape (n_features,)
        Whether missing values were observed in the training data, for each
        feature.
    l2_regularization : float
        The L2 regularization parameter.
    min_hessian_to_split : float, default=1e-3
        The minimum sum of hessians needed in each node. Splits that result in
        at least one child having a sum of hessians less than
        min_hessian_to_split are discarded.
    min_samples_leaf : int, default=20
        The minimum number of samples per leaf.
    min_gain_to_split : float, default=0.0
        The minimum gain needed to split a node. Splits with lower gain will
        be ignored.
    hessians_are_constant: bool, default is False
        Whether hessians are constant.
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    For each feature, find the best bin to split on at a given node.

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        Parameters
        ----------
        n_samples : int
            The number of samples at the node.
        histograms : ndarray of HISTOGRAM_DTYPE of                 shape (n_features, max_bins)
            The histograms of the current node.
        sum_gradients : float
            The sum of the gradients for each sample at the node.
        sum_hessians : float
            The sum of the hessians for each sample at the node.
        value : float
            The bounded value of the current node. We directly pass the value
            instead of re-computing it from sum_gradients and sum_hessians,
            because we need to compute the loss and the gain based on the
            *bounded* value: computing the value from
            sum_gradients / sum_hessians would give the unbounded value, and
            the interaction with min_gain_to_split would not be correct
            anymore. Side note: we can't use the lower_bound / upper_bound
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            children, not the bounds of the current node.
        lower_bound : float
            Lower bound for the children values for respecting the monotonic
            constraints.
        upper_bound : float
            Upper bound for the children values for respecting the monotonic
            constraints.

        Returns
        -------
        best_split_info : SplitInfo
            The info about the best possible split among all features.
        Split samples into left and right arrays.

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        (split_info).

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        array with a given pivot, exactly like a quicksort subroutine.

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        ----------
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            The SplitInfo of the node to split.
        sample_indices : ndarray of unsigned int, shape (n_samples_at_node,)
            The indices of the samples at the node to split. This is a view
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            indices of the left child at the beginning, and the indices of
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            The indices of the samples in the left child. This is a view on
            self.partition.
        right_indices : ndarray of int, shape (n_right_samples,)
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