Scikit-Learn을 이용한 분류와 회귀

 

소스 코드

#분류와 (선형)회귀
import pandas as pd
from sklearn import svm
from sklearn.linear_model import LinearRegression

#y = 2x+1
data = [[0],[2],[5],[7]]
label = [1,5,11,15]
example = [[1],[4]]
print("원하는 결과: 3, 9")

clf = svm.SVC()
clf.fit(data,label)
result = clf.predict(example)
print(result)

lr = LinearRegression()
lr.fit(data,label)
result = lr.predict(example)
print(result)

csv = pd.read_csv('iris.csv')
data2 = csv[["sepal.length","sepal.width","petal.length","petal.width"]]
label2 = csv["variety"]
example2 = [[4.8,3.4,1.6,.2]]

clf.fit(data2,label2)
result = clf.predict(example2)
print(result)

lr = LinearRegression()
lr.fit(data2,label2)
result = lr.predict(example2)
print(result)

실행 결과

원하는 결과: 3, 9
[5 11]
[3. 9.]
[0]
[0.00075935]