TypeError: __init__() got an unexpected keyword argument 'n_iter'

[akashdeepxv]

working on a speaker recognition code and while training the machine getting this:
Exception in Tkinter callback
Traceback (most recent call last):
File "C:\Users\AKASHDEEP\AppData\Local\Programs\Python\Python38\lib\tkinter_init_.py", line 1883, in call
return self.func(*args)
File "C:\Users\AKASHDEEP\AppData\Local\Programs\Python\Python38\Speaker-Recognition\train.py", line 113, in train
traine(v1.get())
File "C:\Users\AKASHDEEP\AppData\Local\Programs\Python\Python38\Speaker-Recognition\GMM1.py", line 40, in traine
gmm = GMM(n_components = 16, n_iter = 200, covariance_type='diag', n_init = 10)
File "C:\Users\AKASHDEEP\AppData\Local\Programs\Python\Python38\lib\site-packages\sklearn\utils\validation.py", line 73, in inner_f
return f(**kwargs)
TypeError: init() got an unexpected keyword argument 'n_iter'

[bjkomer]

Can you provide a minimum example of what causes the error?
From your traceback I don't see hyperopt or hyperopt-sklearn involved at all.

[tanayag]

Faced the same problem, it's coming from SGDRegressor
Here's the example code and traceback;

from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from hpsklearn import HyperoptEstimator, any_regressor, any_preprocessing, svr
from hyperopt import tpe, hp
import math as m

X, y = load_boston().data, load_boston().target
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.2)

model = HyperoptEstimator(regressor=any_regressor('test1_reg'),
                  preprocessing=any_preprocessing('test1_preprocessing'),
                  algo=tpe.suggest,
                  max_evals=5)

model.fit(X_train, y_train, n_folds=3, cv_shuffle=True)

print(model.score(X_test, y_test))
print(mdoel.best_model())

  0%|          | 0/1 [00:00<?, ?trial/s, best loss=?]

job exception: __init__() got an unexpected keyword argument 'n_iter'

  0%|          | 0/1 [00:00<?, ?trial/s, best loss=?]

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-1-452ed9b18bbb> in <module>
     13                   max_evals=5)
     14 
---> 15 model.fit(X_train, y_train, n_folds=3, cv_shuffle=True)
     16 
     17 print(model.score(X_test, y_test))

~/anaconda3/lib/python3.7/site-packages/hpsklearn/estimator.py in fit(self, X, y, EX_list, valid_size, n_folds, cv_shuffle, warm_start, random_state, weights)
    744             increment = min(self.fit_increment,
    745                             adjusted_max_evals - len(self.trials.trials))
--> 746             fit_iter.send(increment)
    747             if filename is not None:
    748                 with open(filename, 'wb') as dump_file:

~/anaconda3/lib/python3.7/site-packages/hpsklearn/estimator.py in fit_iter(self, X, y, EX_list, valid_size, n_folds, cv_shuffle, warm_start, random_state, weights, increment)
    655                               #    so we notice them.
    656                               catch_eval_exceptions=False,
--> 657                               return_argmin=False, # -- in case no success so far
    658                              )
    659             else:

~/anaconda3/lib/python3.7/site-packages/hyperopt/fmin.py in fmin(fn, space, algo, max_evals, timeout, loss_threshold, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin, points_to_evaluate, max_queue_len, show_progressbar)
    480             catch_eval_exceptions=catch_eval_exceptions,
    481             return_argmin=return_argmin,
--> 482             show_progressbar=show_progressbar,
    483         )
    484 

~/anaconda3/lib/python3.7/site-packages/hyperopt/base.py in fmin(self, fn, space, algo, max_evals, timeout, loss_threshold, max_queue_len, rstate, verbose, pass_expr_memo_ctrl, catch_eval_exceptions, return_argmin, show_progressbar)
    684             catch_eval_exceptions=catch_eval_exceptions,
    685             return_argmin=return_argmin,
--> 686             show_progressbar=show_progressbar,
    687         )
    688 

~/anaconda3/lib/python3.7/site-packages/hyperopt/fmin.py in fmin(fn, space, algo, max_evals, timeout, loss_threshold, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin, points_to_evaluate, max_queue_len, show_progressbar)
    507 
    508     # next line is where the fmin is actually executed
--> 509     rval.exhaust()
    510 
    511     if return_argmin:

~/anaconda3/lib/python3.7/site-packages/hyperopt/fmin.py in exhaust(self)
    328     def exhaust(self):
    329         n_done = len(self.trials)
--> 330         self.run(self.max_evals - n_done, block_until_done=self.asynchronous)
    331         self.trials.refresh()
    332         return self

~/anaconda3/lib/python3.7/site-packages/hyperopt/fmin.py in run(self, N, block_until_done)
    284                 else:
    285                     # -- loop over trials and do the jobs directly
--> 286                     self.serial_evaluate()
    287 
    288                 self.trials.refresh()

~/anaconda3/lib/python3.7/site-packages/hyperopt/fmin.py in serial_evaluate(self, N)
    163                 ctrl = base.Ctrl(self.trials, current_trial=trial)
    164                 try:
--> 165                     result = self.domain.evaluate(spec, ctrl)
    166                 except Exception as e:
    167                     logger.error("job exception: %s" % str(e))

~/anaconda3/lib/python3.7/site-packages/hyperopt/base.py in evaluate(self, config, ctrl, attach_attachments)
    890                 self.expr,
    891                 memo=memo,
--> 892                 print_node_on_error=self.rec_eval_print_node_on_error,
    893             )
    894             rval = self.fn(pyll_rval)

~/anaconda3/lib/python3.7/site-packages/hyperopt/pyll/base.py in rec_eval(expr, deepcopy_inputs, memo, max_program_len, memo_gc, print_trace, print_node_on_error)
    909 
    910             try:
--> 911                 rval = scope._impls[node.name](*args, **kwargs)
    912 
    913             except Exception as e:

~/anaconda3/lib/python3.7/site-packages/hpsklearn/components.py in sklearn_SGDRegressor(*args, **kwargs)
     93 @scope.define
     94 def sklearn_SGDRegressor(*args, **kwargs):
---> 95     return sklearn.linear_model.SGDRegressor(*args, **kwargs)
     96 
     97 @scope.define

~/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in inner_f(*args, **kwargs)
     70                           FutureWarning)
     71         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72         return f(**kwargs)
     73     return inner_f
     74 

TypeError: __init__() got an unexpected keyword argument 'n_iter'

I think it's because, there's not agrument in SGDRegressor, 'n_iter'. Instead it's changed to 'max_iter' in the newer versions, as they added an argument for early stopping.

[matcode1]

@tanayag seems to be right, I have tryed to remove SGD and works.