인프런 커뮤니티 질문&답변

파이썬 - 저장되어 있는 데이터로 그래프를 그리고 싶은데 plot 해도 그래프가 나오지 않아 혹시 그래프를 그리고 싶다면 어떤 코딩을  어느 위치에 추가해야 하는지 알수 있을까요 ?

밑에 코딩 첨부하겠습니다.

 

import time

import pymysql

import pandas as pd

import numpy as np

from sklearn.model_selection import train_test_split

import matplotlib.pyplot as plt

groups_folder_path = 'D:/3DP/' #학습데이터 저장 경로

 

A = np.empty((0,5))

D = np.empty((0,4))

mid_D = np.empty((0,4))

 

for indx in range(1,8):

    data_dir = groups_folder_path + 'ACC_' + str(indx) + '.csv'

    data = pd.read_csv(data_dir)

    data = data.to_numpy()

    

    A = np.vstack([A, data])

    data_dir = groups_folder_path + 'DHT_' + str(indx) + '.csv'

    data2 = pd.read_csv(data_dir)

    data2 = data2.to_numpy()

    

    for i in range(0, len(data2)):

        

        dummy = data2[i].reshape([1,4])

        dummy = np.repeat(dummy,repeats = 750, axis = 0)

 

        mid_D = np.vstack([mid_D, dummy])

    

    D = np.vstack([D, mid_D[0:len(data)]])

SS = np.empty((0,6))    

A = np.delete(A,0,1)

D = np.delete(D,0,1)

D = np.delete(D,2,1)

Sum = np.hstack([A,D])

 

for i in range(len(Sum)):

    if Sum[i,3] == 4:

        a = Sum[i]

        a = a.reshape(1,6)

        SS=np.vstack([SS,a])

    else :

        1

 

dummy2 = np.repeat(SS,repeats = 9, axis = 0)

SS = np.vstack([SS,dummy2])

Sum = np.vstack([Sum,SS])

label = Sum[:,3]

label = label.reshape([len(Sum),1])

 

X = np.delete(Sum,3,1)

Y = label

 

 

X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.1,shuffle=True)

 

 

from sklearn.preprocessing import StandardScaler

 

sc = StandardScaler()

sc.fit(X_train)

X_train_std = sc.transform(X_train)

X_test_std = sc.transform(X_test)

 

from sklearn.svm import SVC

 

svm_model = SVC(kernel='rbf',C=5, gamma=0.1, decision_function_shape='ovo')

# ovo = one vs. one / ovr = one vs. rest

svm_model.fit(X_train_std, y_train) # SVM 분류 모델 훈련

 

y_pred = svm_model.predict(X_test_std)

 

q = len(y_test)

L1 = len(y_test[y_test == 1])

L2 = len(y_test[y_test == 2])

L3 = len(y_test[y_test == 3])

L4 = len(y_test[y_test == 4])

 

A1 = 0

A2 = 0

A3 = 0

A4 = 0

A5 = 0

 

 

for i in range (0,len(y_test)):

    if y_pred[i] == y_test[i]:

        if y_pred[i] == 1:

            A1 = A1 + 1

        elif y_pred[i] == 2:

            A2 = A2+1

        elif y_pred[i] == 3:

            A3 = A3+1

        else:

            A4 = A4+1

    else: 

       A5 = A5+1

    

print(A1/L1)

print(A2/L2)

print(A3/L3)

print(A4/L4)

print((len(y_test)-A5)/len(y_test)*100) #최종 정답률

 

from sklearn.metrics import confusion_matrix, plot_confusion_matrix

import matplotlib.pyplot as plt

 

confusion_matrix(y_test, y_pred)