머신러닝.스터디.문제(200414)

 

1	iris data에서 속성 : SL,SW에 대해 (col : 0, 1) 꽃 별로 선형 회귀선 을 그리시오 model : linear regression	https://broscoding.tistory.com/126?category=855525
1-1	iris data에서 속성 : SL,SW에 대해 (col : 0, 1) MSE,RMSE,MAE,model.score(X,y) 를 구하시오 model : linear regression	https://broscoding.tistory.com/126?category=855525
2	wine data file에서 (sklearn load 아님 numpy loadtxt) winequality-red model : linear regression 을 이용해서 등급을 예측하기 위해 데이터를 정규화 한뒤 w(coef) b(intercept) 를 구하시오 (정규화,다차원데이터)	https://broscoding.tistory.com/127
3	data : make_prop class : 2 model : logistic graph : mglearn 영역 색칠하기	400,2,[[0,0],[5,5]],[2,3] https://broscoding.tistory.com/entry/%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9DlinearmodelLogisticRegression%EB%A1%9C%EC%A7%80%EC%8A%A4%ED%8B%B1-%ED%9A%8C%EA%B7%80
4	data : make_prop class : 3 model : logistic graph : mglearn guide line 그리기 영역 색칠하기	300,2,[[0,0],[-10,10],[10,10]],[2,3,5] https://broscoding.tistory.com/entry/%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9DlinearmodelLogisticRegressionClass3
5	data: iris feature : (col : 0, 1) class : setosa =0, others=1 model : SVM  graph : gmlearn 영역 색칠하기	https://broscoding.tistory.com/entry/%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9DLinear-SVM%EC%84%A0%ED%98%95-%EC%84%9C%ED%8F%AC%ED%8A%B8%EB%B2%A1%ED%84%B0%EB%A8%B8%EC%8B%A0-%EA%B8%B0%EC%B4%88