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 How to arrange the four pictures of a matplotlib.pyplot? vokoyo Silly Frenchman Posts: 20 Threads: 12 Joined: Apr 2018 Reputation: 0 Likes received: 0 #1 Apr-04-2019, 10:58 PM (This post was last modified: Apr-04-2019, 10:58 PM by vokoyo. Edited 2 times in total. Edit Reason: Title, Formatting ) May I know how to modify my Python programming so that can arrange the pictures - from sklearn import datasets #load data iris=datasets.load_iris() X=iris.data[:,[2,3]] y=iris.target from sklearn.model_selection import train_test_split X_train, X_test,y_train, y_test=train_test_split(X,y,test_size=0.3, random_state=1) #feature scaling 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) # set outlier X_train_std[0]=(1,-1) #define plot_decision_regions from matplotlib.colors import ListedColormap import matplotlib.pyplot as plt import numpy as np def plot_decision_regions(X, y, classifier,test_idx = None, resolution=0.02): markers = ('s','x','o','^','v') colors = ('red','blue','lightgreen','gray','cyan') cmap = ListedColormap(colors[: len(np.unique(y))]) x1_min, x1_max = X[:,0].min() -1, X[:,0].max()+1 x2_min, x2_max = X[:,1].min() -1, X[:,1].max()+1 xx1, xx2 = np.meshgrid(np.arange(x1_min,x1_max,resolution), np.arange(x2_min,x2_max,resolution)) Z = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T) Z = Z.reshape(xx1.shape) plt.contourf(xx1, xx2, Z, alpha=0.4, cmap=cmap) plt.xlim(xx1.min(), xx1.max()) plt.ylim(xx2.min(), xx2.max()) print(np.unique(y)) for idx, cl in enumerate(np.unique(y)): plt.scatter(x=X[y==cl, 0], y=X[y==cl, 1], alpha=0.8, c=cmap(idx), marker = markers[idx],label = cl,edgecolor='black') #SVM from sklearn.svm import SVC C=[] X_combined_std = np.vstack((X_train_std, X_test_std)) y_combined = np.hstack((y_train, y_test)) #draw figure fig=plt.subplots(nrows=2, ncols=2,figsize=(10,5)) for c in np.arange(-1,3): svm=SVC(kernel='linear',C=10.**c, random_state=0) svm.fit(X_train_std,y_train) plot_decision_regions(X_combined_std,y_combined,classifier=svm, test_idx=range(105, 150)) plt.xlabel('petal lengh[standardized]') plt.ylabel('petal width[standardized]') plt.title('C='+str(10.**c)) plt.legend(loc='upper left') plt.tight_layout() plt.show() Please see the attached image picture - I get the answer but not sure how to put together the four pictures « Next Oldest | Next Newest »

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