from sklearn.linear_model import LogisticRegression

regressor = LogisticRegression(solver='saga', C=(10 ** (-3)), fit_intercept=False, n_jobs=40)
regressor.fit(X_train_one_hot, y_train.values)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<timed exec> in <module>

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/linear_model/_logistic.py in fit(self, X, y, sample_weight)
   1404         else:
   1405             prefer = 'processes'
-> 1406         fold_coefs_ = Parallel(n_jobs=self.n_jobs, verbose=self.verbose,
   1407                                **_joblib_parallel_args(prefer=prefer))(
   1408             path_func(X, y, pos_class=class_, Cs=[C_],

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/joblib/parallel.py in __call__(self, iterable)
   1052 
   1053             with self._backend.retrieval_context():
-> 1054                 self.retrieve()
   1055             # Make sure that we get a last message telling us we are done
   1056             elapsed_time = time.time() - self._start_time

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/joblib/parallel.py in retrieve(self)
    931             try:
    932                 if getattr(self._backend, 'supports_timeout', False):
--> 933                     self._output.extend(job.get(timeout=self.timeout))
    934                 else:
    935                     self._output.extend(job.get())

~/.pyenv/versions/3.9.5/lib/python3.9/multiprocessing/pool.py in get(self, timeout)
    769             return self._value
    770         else:
--> 771             raise self._value
    772 
    773     def _set(self, i, obj):

~/.pyenv/versions/3.9.5/lib/python3.9/multiprocessing/pool.py in worker(inqueue, outqueue, initializer, initargs, maxtasks, wrap_exception)
    123         job, i, func, args, kwds = task
    124         try:
--> 125             result = (True, func(*args, **kwds))
    126         except Exception as e:
    127             if wrap_exception and func is not _helper_reraises_exception:

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/joblib/_parallel_backends.py in __call__(self, *args, **kwargs)
    593     def __call__(self, *args, **kwargs):
    594         try:
--> 595             return self.func(*args, **kwargs)
    596         except KeyboardInterrupt as e:
    597             # We capture the KeyboardInterrupt and reraise it as

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/joblib/parallel.py in __call__(self)
    260         # change the default number of processes to -1
    261         with parallel_backend(self._backend, n_jobs=self._n_jobs):
--> 262             return [func(*args, **kwargs)
    263                     for func, args, kwargs in self.items]
    264 

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/joblib/parallel.py in <listcomp>(.0)
    260         # change the default number of processes to -1
    261         with parallel_backend(self._backend, n_jobs=self._n_jobs):
--> 262             return [func(*args, **kwargs)
    263                     for func, args, kwargs in self.items]
    264 

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/utils/fixes.py in __call__(self, *args, **kwargs)
    220     def __call__(self, *args, **kwargs):
    221         with config_context(**self.config):
--> 222             return self.function(*args, **kwargs)

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/linear_model/_logistic.py in _logistic_regression_path(X, y, pos_class, Cs, fit_intercept, max_iter, tol, verbose, solver, coef, class_weight, dual, penalty, intercept_scaling, multi_class, random_state, check_input, max_squared_sum, sample_weight, l1_ratio)
    796                 beta = (1. / C) * l1_ratio
    797 
--> 798             w0, n_iter_i, warm_start_sag = sag_solver(
    799                 X, target, sample_weight, loss, alpha,
    800                 beta, max_iter, tol,

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/utils/validation.py in inner_f(*args, **kwargs)
     61             extra_args = len(args) - len(all_args)
     62             if extra_args <= 0:
---> 63                 return f(*args, **kwargs)
     64 
     65             # extra_args > 0

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/linear_model/_sag.py in sag_solver(X, y, sample_weight, loss, alpha, beta, max_iter, tol, verbose, random_state, check_input, max_squared_sum, warm_start_mem, is_saga)
    296         num_seen_init = 0
    297 
--> 298     dataset, intercept_decay = make_dataset(X, y, sample_weight, random_state)
    299 
    300     if max_squared_sum is None:

~/.cache/pypoetry/virtualenvs/market-making-O6Kn0-Jh-py3.9/lib/python3.9/site-packages/sklearn/linear_model/_base.py in make_dataset(X, y, sample_weight, random_state)
     91 
     92     if sp.issparse(X):
---> 93         dataset = CSRData(X.data, X.indptr, X.indices, y, sample_weight,
     94                           seed=seed)
     95         intercept_decay = SPARSE_INTERCEPT_DECAY

sklearn/utils/_seq_dataset.pyx in sklearn.utils._seq_dataset.CSRDataset64.__cinit__()

ValueError: Buffer dtype mismatch, expected 'int' but got 'long'