Test cases fail due to ValueErrror

[kimusaku]

Describe the bug
Currently, executing pytest causes ValueError.

To Reproduce
run the following command on main branch:

pytest -k test_classifier_category_binary_num_proba[target_category_binary_num-auc]

script

_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/sapientml/test_generatedcode.py:107: in _execute
    generator.generate_pipeline(dataset, task)
sapientml_core/generator.py:219: in generate_pipeline
    dataset, sapientml_results = self.generate_code(dataset, task)
sapientml_core/generator.py:265: in generate_code
    dataset_summary = summarize_dataset(df, task)  # type: ignore
sapientml_core/params.py:403: in summarize_dataset
    meta_features_m = generate_model_meta_features(df_train, task.target_columns, is_clf_task)
sapientml_core/meta_features.py:1178: in generate_model_meta_features
    meta_feature_dict = _collect_model_meta_features(user_training, target_column_name)
sapientml_core/meta_features.py:275: in _collect_model_meta_features
    feature_dict.update(_collect_csv_column_with_ttest(dataX, datay[catg_target_columns]))
sapientml_core/meta_features.py:495: in _collect_csv_column_with_ttest
    p = _get_ttest_pvalue(column, yc)
sapientml_core/meta_features.py:455: in _get_ttest_pvalue
    _, p = scipy.stats.ttest_ind(c1, c2, equal_var=False)
venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_axis_nan_policy.py:573: in axis_nan_policy_wrapper
    res = hypotest_fun_out(*samples, **kwds)
venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:7005: in ttest_ind
    v1 = _var(a, axis, ddof=1)
venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:1110: in _var
    var = _moment(x, 2, axis, mean=mean, xp=xp)
venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:1080: in _moment
    eps = xp.finfo(dtype).eps * 10
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

cls = <class 'numpy.finfo'>, dtype = <class 'numpy.bool_'>

    def __new__(cls, dtype):
        try:
            obj = cls._finfo_cache.get(dtype)  # most common path
            if obj is not None:
                return obj
        except TypeError:
            pass
    
        if dtype is None:
            # Deprecated in NumPy 1.25, 2023-01-16
            warnings.warn(
                "finfo() dtype cannot be None. This behavior will "
                "raise an error in the future. (Deprecated in NumPy 1.25)",
                DeprecationWarning,
                stacklevel=2
            )
    
        try:
            dtype = numeric.dtype(dtype)
        except TypeError:
            # In case a float instance was given
            dtype = numeric.dtype(type(dtype))
    
        obj = cls._finfo_cache.get(dtype)
        if obj is not None:
            return obj
        dtypes = [dtype]
        newdtype = numeric.obj2sctype(dtype)
        if newdtype is not dtype:
            dtypes.append(newdtype)
            dtype = newdtype
        if not issubclass(dtype, numeric.inexact):
>           raise ValueError("data type %r not inexact" % (dtype))
E           ValueError: data type <class 'numpy.bool_'> not inexact

venv-split-before-transform/lib/python3.10/site-packages/numpy/core/getlimits.py:516: ValueError


==================================================================== short test summary info =====================================================================
FAILED tests/sapientml/test_generatedcode.py::test_classifier_category_binary_num_proba[target_category_binary_num-auc] - ValueError: data type <class 'numpy.bool_'> not inexact

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