fix: correctly call predict for OLS in CUPAC

[mnicky]

OLS predict() should be called on the fitted model.

At least in my environment, the original version ends with an exception:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[59], line 1
----> 1 ab_test_cupac = ABTest(abtest, ab_params).cupac()

File /opt/conda/envs/py311/lib/python3.11/site-packages/abacus/auto_ab/abtest.py:668, in ABTest.cupac(self)
    666 self.__check_required_metric_type("cupac")
    667 self.__check_required_columns(self.__dataset, "cupac")
--> 668 result_df = VarianceReduction.cupac(
    669     self.__dataset,
    670     target_prev_col=self.params.data_params.target_prev,
    671     target_now_col=self.params.data_params.target,
    672     factors_prev_cols=self.params.data_params.predictors_prev,
    673     factors_now_cols=self.params.data_params.predictors_now,
    674     groups_col=self.params.data_params.group_col,
    675 )
    677 params_new = copy.deepcopy(self.params)
    678 params_new.data_params.control = self.__get_group(
    679     self.params.data_params.control_name, result_df
    680 )

File /opt/conda/envs/py311/lib/python3.11/site-packages/abacus/auto_ab/variance_reduction.py:98, in VarianceReduction.cupac(cls, x, target_prev_col, target_now_col, factors_prev_cols, factors_now_cols, groups_col)
     79 """Perform CUPED on target variable with covariate calculated
     80 as a prediction from a linear regression model.
     81 
   (...)
     93     pandas.DataFrame: Pandas DataFrame with additional columns: target_pred and target_now_cuped
     94 """
     95 x = cls._target_encoding(
     96     x, list(set(factors_prev_cols + factors_now_cols)), target_prev_col
     97 )
---> 98 x.loc[:, "target_pred"] = cls._predict_target(
     99     x, target_prev_col, factors_prev_cols, factors_now_cols
    100 )
    101 x_new = cls.cuped(x, target_now_col, groups_col, "target_pred")
    102 return x_new

Cell In[58], line 30, in predict_target(x, target_prev_col, factors_prev_cols, factors_now_cols)
     27 print(results.summary())
     28 x_predict = x[factors_now_cols]
---> 30 return model.predict(x_predict)

File /opt/conda/envs/py311/lib/python3.11/site-packages/statsmodels/regression/linear_model.py:411, in RegressionModel.predict(self, params, exog)
    408 if exog is None:
    409     exog = self.exog
--> 411 return np.dot(exog, params)

File <__array_function__ internals>:200, in dot(*args, **kwargs)

ValueError: shapes (2400372,5) and (2400372,5) not aligned: 5 (dim 1) != 2400372 (dim 0)