Useful example for illustrating machine learning algorithms based on MNIST data
We only include a randomly selected set of 2s and 7s along with the two predictors based on the proportion of dark pixels in the upper left and lower right quadrants respectively. The dataset is divided into training and test sets.
data(mnist_27)
An object of class list.
train. A data frame containing training data: labels and predictors.
test. A data frame containing test data: labels and predictors.
index_train. The index of the original mnist training data used for the training set.
index_test. The index of the original mnist test data used for the test set.
true_p. A data.frame containing the
two predictors x_1 and x_2 and the conditional probability of being a 7
for x_1, x_2.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998.
[read_mnist()]
data(mnist_27) with(mnist_27$train, plot(x_1, x_2, col = as.numeric(y)))
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