显示 100 mnist 数据集

如何解决显示 100 mnist 数据集

这是我用来打印 100 mnist 数据的原始未缩小图片的代码，但它不断给我一个错误。即使在尝试了很多之后，我也找不到解决方案。征求建议

 from sklearn.datasets import fetch_openml
   mnist = fetch_openml('mnist_784')
   X = mnist["data"]
   y = mnist["target"]
   X_train,X_test,y_train,y_test = X[:60000],X[60000:],y[:60000],y[60000:]
   pca = PCA()
   pca.fit(X_train)
   cumsum = np.cumsum(pca.explained_variance_ratio_)
   d = np.argmax(cumsum >= 0.90) + 1

   #Setup a figure 8 inches by 8 inches
   fig = plt.figure(figsize=(8,8))
   fig.subplots_adjust(left=0,right=1,bottom=0,top=1,hspace=0.05,wspace=0.05)
    for i in range(100):
        ax = fig.add_subplot(10,10,i+1,xticks=[],yticks=[])
        ax.imshow(X_train[i].reshape(28,28),cmap=plt.cm.bone,interpolation='nearest')
        plt.show()

解决方法

这正是您的情节显示语句仍在循环中的地方。只需将其移出循环，它就会显示正常。试试下面的内容；

from sklearn.datasets import fetch_openml
from sklearn.decomposition import PCA
from sklearn.model_selection import train_test_split
import numpy as np
import matplotlib.pyplot as plt

mnist = fetch_openml('mnist_784')
X = mnist["data"]
y = mnist["target"]
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.20,random_state=44)
pca = PCA()
pca.fit(X_train)

fig = plt.figure(figsize=(8,8))
fig.subplots_adjust(left=0,right=1,bottom=0,top=1,hspace=0.05,wspace=0.05)
for i in range(100):
    ax = fig.add_subplot(10,10,i+1,xticks=[],yticks=[])
    ax.imshow(X_train[i].reshape(28,28),cmap=plt.cm.bone,interpolation='nearest')

plt.show()

,

import matplotlib.pyplot as plt

fig,ax = plt.subplots(5,10)

for i in range(10):
    for j in range(10):
      ax[i,j].imshow(X_train[(10*i)+j].reshape(8,8),cmap='binary')