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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)%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)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 ')'View.MemoryView.memoryview.convert_item_to_objectView.MemoryView._memoryviewslice.convert_item_to_objectAcquisition count is %d (line %d)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_sliceView.MemoryView.Enum.__reduce_cython__View.MemoryView.memoryview_fromsliceView.MemoryView.memoryview_copy_from_sliceView.MemoryView.memoryview.__repr__value too large to convert to intvalue too large to convert to unsigned charcan't convert negative value to unsigned charc-string too long to convert to PythonCannot convert %.200s to %.200sView.MemoryView.get_slice_from_memviewView.MemoryView.memoryview.is_f_contigView.MemoryView.memoryview.is_c_contigView.MemoryView.assert_direct_dimensionsView.MemoryView.memoryview.setitem_slice_assign_scalar'NoneType' object is not subscriptablehasattr(): attribute name must be stringView.MemoryView.__pyx_unpickle_Enum__set_stateView.MemoryView.Enum.__setstate_cython__sklearn/ensemble/_hist_gradient_boosting/_predictor.pyxsklearn.ensemble._hist_gradient_boosting._predictor._predict_from_numeric_dataCannot 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.copyinteger division or modulo by zerovalue too large to perform divisionView.MemoryView.pybuffer_indexView.MemoryView.memoryview.get_item_pointerView.MemoryView.__pyx_unpickle_Enumtoo many values to unpack (expected %zd)need more than %zd value%.1s to unpack'NoneType' object is not iterableView.MemoryView.memoryview.__setitem__sklearn.ensemble._hist_gradient_boosting._predictor._predict_from_binned_dataView.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._predictor._compute_partial_dependenceView.MemoryView.memoryview.__cinit__View.MemoryView.memoryview.setitem_slice_assignmentAll dimensions preceding dimension %d must be indexed and not slicedView.MemoryView.slice_memviewsliceStep may not be zero (axis %d)View.MemoryView.memoryview.__getitem__sklearn.ensemble._hist_gradient_boosting._predictorcompiletime version %s of module '%.100s' does not match runtime version %s_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._predictorsklearn.ensemble._hist_gradient_boosting._predictor._memoryviewsliceInternal class for passing memoryview slices to Pythonsklearn.ensemble._hist_gradient_boosting._predictor.memoryviewsklearn.ensemble._hist_gradient_boosting._predictor.Enumsklearn.ensemble._hist_gradient_boosting._predictor.arrayð?+‡ÙÎ÷ï?j¼t“ð?
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-"VWfWvW†W–W¦W¶WÆWÖWæWöWXX&X6XFXVXfXvX†X–X¦X¶XÆXÖXæXöXYY&Y6YFYVYfYvY†Y–Y¦Y¶YÆYÖYæYöYZZ&Z6ZFZVZfZvZ†Z–Z¦Z¶ZÆZÖZæZöZ[[&[6[F[V[f[v[†[–[¦[¶[Æ[Ö[æ[ö[\\&\6\F\V\f\v\†\–\¦\¶\Æ\Ö\æ\ö\]]&]6]F]V]f]v]†]–]¦]¶]Æ]Ö]æ]ö]^^&^6^F^V^f^v^†^–^¦^¶^Æ^Ö^æ^ö^__&_6_F_ 4"Partial dependence of the response on the ``target_features`` set.

    For each sample in ``X`` a tree traversal is performed.
    Each traversal starts from the root with weight 1.0.

    At each non-leaf node that splits on a target feature, either
    the left child or the right child is visited based on the feature
    value of the current sample, and the weight is not modified.
    At each non-leaf node that splits on a complementary feature,
    both children are visited and the weight is multiplied by the fraction
    of training samples which went to each child.

    At each leaf, the value of the node is multiplied by the current
    weight (weights sum to 1 for all visited terminal nodes).

    Parameters
    ----------
    nodes : view on array of PREDICTOR_RECORD_DTYPE, shape (n_nodes)
        The array representing the predictor tree.
    X : view on 2d ndarray, shape (n_samples, n_target_features)
        The grid points on which the partial dependence should be
        evaluated.
    target_features : view on 1d ndarray, shape (n_target_features)
        The set of target features for which the partial dependence
        should be evaluated.
    out : view on 1d ndarray, shape (n_samples)
        The value of the partial dependence function on each grid
        point.
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