質問編集履歴
3
title
CHANGED
|
File without changes
|
body
CHANGED
|
@@ -8,9 +8,6 @@
|
|
|
8
8
|
|
|
9
9
|
```ここに言語を入力
|
|
10
10
|
import pandas as pd
|
|
11
|
-
sample_submission = pd.read_csv("../input/nlp-getting-started/sample_submission.csv")
|
|
12
|
-
test = pd.read_csv("../input/nlp-getting-started/test.csv")
|
|
13
|
-
train = pd.read_csv("../input/nlp-getting-started/train.csv")
|
|
14
11
|
df=train
|
|
15
12
|
|
|
16
13
|
from sklearn.preprocessing import LabelEncoder
|
2
修正
title
CHANGED
|
File without changes
|
body
CHANGED
|
@@ -46,5 +46,111 @@
|
|
|
46
46
|
gscv.best_params_
|
|
47
47
|
```
|
|
48
48
|
```ここに言語を入力
|
|
49
|
+
---------------------------------------------------------------------------
|
|
50
|
+
ValueError Traceback (most recent call last)
|
|
51
|
+
<ipython-input-10-e418a6eefe52> in <module>
|
|
52
|
+
14 scoring="accuracy",cv=3
|
|
53
|
+
15 )
|
|
54
|
+
---> 16 gscv.fit(X_train,y_train)
|
|
55
|
+
17 gscv.best_params_
|
|
56
|
+
|
|
57
|
+
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_search.py in fit(self, X, y, groups, **fit_params)
|
|
58
|
+
686 return results
|
|
59
|
+
687
|
|
60
|
+
--> 688 self._run_search(evaluate_candidates)
|
|
61
|
+
689
|
|
62
|
+
690 # For multi-metric evaluation, store the best_index_, best_params_ and
|
|
63
|
+
|
|
64
|
+
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_search.py in _run_search(self, evaluate_candidates)
|
|
65
|
+
1147 def _run_search(self, evaluate_candidates):
|
|
66
|
+
1148 """Search all candidates in param_grid"""
|
|
67
|
+
-> 1149 evaluate_candidates(ParameterGrid(self.param_grid))
|
|
68
|
+
1150
|
|
69
|
+
1151
|
|
70
|
+
|
|
71
|
+
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_search.py in evaluate_candidates(candidate_params)
|
|
72
|
+
665 for parameters, (train, test)
|
|
73
|
+
666 in product(candidate_params,
|
|
74
|
+
--> 667 cv.split(X, y, groups)))
|
|
75
|
+
668
|
|
76
|
+
669 if len(out) < 1:
|
|
77
|
+
|
|
78
|
+
/opt/conda/lib/python3.6/site-packages/joblib/parallel.py in __call__(self, iterable)
|
|
79
|
+
1001 # remaining jobs.
|
|
80
|
+
1002 self._iterating = False
|
|
81
|
+
-> 1003 if self.dispatch_one_batch(iterator):
|
|
82
|
+
1004 self._iterating = self._original_iterator is not None
|
|
83
|
+
1005
|
|
84
|
+
|
|
85
|
+
/opt/conda/lib/python3.6/site-packages/joblib/parallel.py in dispatch_one_batch(self, iterator)
|
|
86
|
+
832 return False
|
|
87
|
+
833 else:
|
|
88
|
+
--> 834 self._dispatch(tasks)
|
|
89
|
+
835 return True
|
|
90
|
+
836
|
|
91
|
+
|
|
92
|
+
/opt/conda/lib/python3.6/site-packages/joblib/parallel.py in _dispatch(self, batch)
|
|
93
|
+
751 with self._lock:
|
|
94
|
+
752 job_idx = len(self._jobs)
|
|
95
|
+
--> 753 job = self._backend.apply_async(batch, callback=cb)
|
|
96
|
+
754 # A job can complete so quickly than its callback is
|
|
97
|
+
755 # called before we get here, causing self._jobs to
|
|
98
|
+
|
|
99
|
+
/opt/conda/lib/python3.6/site-packages/joblib/_parallel_backends.py in apply_async(self, func, callback)
|
|
100
|
+
199 def apply_async(self, func, callback=None):
|
|
101
|
+
200 """Schedule a func to be run"""
|
|
102
|
+
--> 201 result = ImmediateResult(func)
|
|
103
|
+
202 if callback:
|
|
104
|
+
203 callback(result)
|
|
105
|
+
|
|
106
|
+
/opt/conda/lib/python3.6/site-packages/joblib/_parallel_backends.py in __init__(self, batch)
|
|
107
|
+
580 # Don't delay the application, to avoid keeping the input
|
|
108
|
+
581 # arguments in memory
|
|
109
|
+
--> 582 self.results = batch()
|
|
110
|
+
583
|
|
111
|
+
584 def get(self):
|
|
112
|
+
|
|
113
|
+
/opt/conda/lib/python3.6/site-packages/joblib/parallel.py in __call__(self)
|
|
114
|
+
254 with parallel_backend(self._backend, n_jobs=self._n_jobs):
|
|
115
|
+
255 return [func(*args, **kwargs)
|
|
116
|
+
--> 256 for func, args, kwargs in self.items]
|
|
117
|
+
257
|
|
118
|
+
258 def __len__(self):
|
|
119
|
+
|
|
120
|
+
/opt/conda/lib/python3.6/site-packages/joblib/parallel.py in <listcomp>(.0)
|
|
121
|
+
254 with parallel_backend(self._backend, n_jobs=self._n_jobs):
|
|
122
|
+
255 return [func(*args, **kwargs)
|
|
123
|
+
--> 256 for func, args, kwargs in self.items]
|
|
124
|
+
257
|
|
125
|
+
258 def __len__(self):
|
|
126
|
+
|
|
127
|
+
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_validation.py in _fit_and_score(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, return_n_test_samples, return_times, return_estimator, error_score)
|
|
128
|
+
514 estimator.fit(X_train, **fit_params)
|
|
129
|
+
515 else:
|
|
130
|
+
--> 516 estimator.fit(X_train, y_train, **fit_params)
|
|
131
|
+
517
|
|
132
|
+
518 except Exception as e:
|
|
133
|
+
|
|
134
|
+
/opt/conda/lib/python3.6/site-packages/xgboost/sklearn.py in fit(self, X, y, sample_weight, eval_set, eval_metric, early_stopping_rounds, verbose, xgb_model, sample_weight_eval_set, callbacks)
|
|
135
|
+
724 else:
|
|
136
|
+
725 train_dmatrix = DMatrix(X, label=training_labels,
|
|
137
|
+
--> 726 missing=self.missing, nthread=self.n_jobs)
|
|
138
|
+
727
|
|
139
|
+
728 self._Booster = train(xgb_options, train_dmatrix, self.get_num_boosting_rounds(),
|
|
140
|
+
|
|
141
|
+
/opt/conda/lib/python3.6/site-packages/xgboost/core.py in __init__(self, data, label, missing, weight, silent, feature_names, feature_types, nthread)
|
|
142
|
+
402 self._init_from_csc(data)
|
|
143
|
+
403 elif isinstance(data, np.ndarray):
|
|
144
|
+
--> 404 self._init_from_npy2d(data, missing, nthread)
|
|
145
|
+
405 elif isinstance(data, DataTable):
|
|
146
|
+
406 self._init_from_dt(data, nthread)
|
|
147
|
+
|
|
148
|
+
/opt/conda/lib/python3.6/site-packages/xgboost/core.py in _init_from_npy2d(self, mat, missing, nthread)
|
|
149
|
+
476 # we try to avoid data copies if possible (reshape returns a view when possible
|
|
150
|
+
477 # and we explicitly tell np.array to try and avoid copying)
|
|
151
|
+
--> 478 data = np.array(mat.reshape(mat.size), copy=False, dtype=np.float32)
|
|
152
|
+
479 handle = ctypes.c_void_p()
|
|
153
|
+
480 missing = missing if missing is not None else np.nan
|
|
154
|
+
|
|
49
155
|
ValueError: setting an array element with a sequence.
|
|
50
156
|
```
|
1
修正
title
CHANGED
|
File without changes
|
body
CHANGED
|
@@ -1,5 +1,3 @@
|
|
|
1
|
-
自然言語処理に取り組んでおります。
|
|
2
|
-
|
|
3
1
|
以下のコードを書いておりますが、
|
|
4
2
|
最後の「# GBDTモデルのパラメータ探索」以降のコード入力追加で、
|
|
5
3
|
以下のようなエラー（setting an array element with a sequence.）が出ます。
|