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์ง๋ฌธ ๋๋ฆฝ๋๋ค. Quiz ๋ต์์ ์คํ์ ์๋ฌ ๋ฐ์์์ธ์ ์๊ณ ์ถ์ต๋๋ค.
๊ธฐ์ถ๋ฌธ์ ์๋ฌ ์์ธ์ ์๊ณ ์ถ์ต๋๋ค. (์ฌ์ง)
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Q&A
๋ถ๋ฅ ์์ธก์์ ๊ฒฐ๊ณผ๊ฐ์ ๊ตฌ์ฒด์ ๋ด์ฉ์ ํ์ธํ ์ ์๋์ง์?
์ ์๋, ๊ฐ์ฌํฉ๋๋ค. ๋ถ๋ฅ๋ฌธ์ ์ ๋ผ๋ฒจ์ธ์ฝ๋ฉ์ ์๋ฌ ๋ฉ์์ง์ ์์ธ ๋ฐ ํด๊ฒฐ์ ํ๊ณ ์ถ์ต๋๋ค. from sklearn.preprocessing import LabelEncoder X_label = ['sex', 'embarked', 'class', 'who', 'adult_male', 'deck', 'embark_town', 'alone'] X_train[label] = X_train[label].apply(LabelEncoder().fit_transform) X_test[label] = X_test[label].apply(LabelEncoder().fit_transform) print(X_train.head()) [์๋ฌ ๋ฉ์์ง] ypeError Traceback (most recent call last) C:\ProgramData\Anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode(values, uniques, encode, check_unknown) 111 try: --> 112 res = _encode_python(values, uniques, encode) 113 except TypeError: C:\ProgramData\Anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode_python(values, uniques, encode) 59 if uniques is None: ---> 60 uniques = sorted(set(values)) 61 uniques = np.array(uniques, dtype=values.dtype) TypeError: 'TypeError Traceback (most recent call last) in 1 from sklearn.preprocessing import LabelEncoder 2 X_label = ['sex', 'embarked', 'class', 'who', 'adult_male', 'deck', 'embark_town', 'alone'] ----> 3 X_train[label] = X_train[label].apply(LabelEncoder().fit_transform) 4 X_test[label] = X_test[label].apply(LabelEncoder().fit_transform) 5 print(X_train.head()) C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.py in apply(self, func, axis, raw, result_type, args, **kwds) 6876 kwds=kwds, 6877 ) -> 6878 return op.get_result() 6879 6880 def applymap(self, func) -> "DataFrame": C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\apply.py in get_result(self) 184 return self.apply_raw() 185 --> 186 return self.apply_standard() 187 188 def apply_empty_result(self): C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\apply.py in apply_standard(self) 311 312 # compute the result using the series generator --> 313 results, res_index = self.apply_series_generator() 314 315 # wrap results C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\apply.py in apply_series_generator(self) 339 else: 340 for i, v in enumerate(series_gen): --> 341 results[i] = self.f(v) 342 keys.append(v.name) 343 C:\ProgramData\Anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in fit_transform(self, y) 250 """ 251 y = column_or_1d(y, warn=True) --> 252 self.classes_, y = _encode(y, encode=True) 253 return y 254 C:\ProgramData\Anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode(values, uniques, encode, check_unknown) 112 res = _encode_python(values, uniques, encode) 113 except TypeError: --> 114 raise TypeError("argument must be a string or number") 115 return res 116 else: TypeError: argument must be a string or number
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Q&A
์ง๋ฌธ ๋๋ฆฝ๋๋ค. Quiz ๋ต์์ ์คํ์ ์๋ฌ ๋ฐ์์์ธ์ ์๊ณ ์ถ์ต๋๋ค.
์ข์ ๊ฐ์ ์ฌ์ฐจ ๊ฐ์ฌ๋๋ฆฝ๋๋ค. ๋จธ์ ๋ฌ๋์ ๊ฒฝ์ฒญํ๋ฉด์ ์ง๋ฌธ์ด ์์ด ์ฌ๋ ธ์ต๋๋ค. ํ๊ท๋ชจํ์์์ ํ๊ฐ์งํ๊ฐ R-์ ๊ณฑ, RMSE, RAE, MSE๋ก ํ๊ฐํ์ง ์๋์ง์? ๋ฌธ์ ์์, ์๋ก์ด ๊ฐ์ ์์ธก๊ฐ์ ๋ฌธ์ ๊ฐ ๋์จ๋ค๋ฉด ๋์๋ฐฉ๋ฒ ๋ถํ๋๋ฆฝ๋๋ค. ML_bigineer2๊น์ง ํ๊ฐ ์ฒ๋๊ฐ Confusion matix์ ๋ถ๋ฅ์ ํ๋๋ก ๋ต์์ด ์์ฑ๋๋ ๊ฒ ๊ฐ์ ๊ถ๊ธํ์ฌ ์ง๋ฌธ์ ๋๋ฆฝ๋๋ค.
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