(centers == new_centers): break centers = new_centers return centers, labels from sklearn.datasets import fetch_openml mnist = fetch_openml('mnist_784', version=1) mnist.data.shape X= mnist["data"].to_numpy() X.shape import matplotlib as mpl import matplotlib.pyplot as plt fig, ax ...
MNIST 数据集:MNIST数据集是一个手写数字的图像数据集,包含了60,000个训练样本和10,000个测试样本。该数据集经常被用来训练和测试图像识别模型。下面是一个加载和查看MNIST数据集的代码示例: fromsklearn.datasetsimportfetch_openml mnist=fetch_openml('mnist_784')print(mnist.data)# 打印数据集的特征矩阵print(...
datasets import fetch_openml mnist = fetch_openml('mnist_784', version=1, cache=True) mnist.target = mnist.target.astype(np.int8) # fetch_openml() returns targets as strings sort_by_target(mnist) # fetch_openml() returns an unsorted dataset except ImportError: from sklearn.datasets impo...
import matplotlib.pyplot as plt from sklearn.datasets import fetch_openml Download MNIST dataset: mnist = fetch_openml('mnist_784', version=1) mnist.keys() U0, v0 = mnist["data"], mnist["target"] U = U0.astype(np.double) # changes the attribute values to ...