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Python3

K-NN Study import numpy as np import matplotlib.pyplot as plt from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split fish_length = [25.4, 26.3, 26.5, 29.0, 29.0, 29.7, 29.7, 30.0, 30.0, 30.7, 31.0, 31.0, 31.5, 32.0, 32.0, 32.0, 33.0, 33.0, 33.5, 33.5, 34.0, 34.0, 34.5, 35.0, 35.0, 35.0, 35.0, 36.0, 36.0, 37.0, 38.5, 38.5, 39.5, 41.0, 41.0, 9.8, 10.5, 10.6, 1.. 2022. 4. 18.
Linear Regression Study import numpy as np import matplotlib.pyplot as plt import pandas as pd from sklearn.neighbors import KNeighborsClassifier from sklearn.neighbors import KNeighborsRegressor from sklearn.linear_model import LinearRegression from sklearn.model_selection import train_test_split perch_length = np.array( [8.4, 13.7, 15.0, 16.2, 17.4, 18.0, 18.7, 19.0, 19.6, 20.0, 21.0, 21.0, 21.0, 21.3, 22.0, 22.0, 22.. 2022. 4. 17.
Python) 리스트(list) 조작 함수 리스트(list) 조작 함수 list datatype 조작 함수 설명 Code List = [12, 54, 34, 66, 10, 9, 5] # append(...) List.append(100) # 뒤에 100을 추가 print(" After append(100) : %s"% List) # pop() List.pop() # 가장 뒤의 원소를 제거 print(" After pop() : %s"% List) # sort() List.sort() # 정렬 (Default : 오름차순) print(" After sort() : %s"% List) # reverse() List.reverse() # 현재 list를 역순으로 뒤집는다. print(" After reverse() : %s"% List) # inser.. 2022. 1. 7.
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