Performance assessment with training data

The code for obtaining the loss, accuracy, and confusion matrix based on the training data is as follows:

# Loss and accuracymodel %>% evaluate(trainx, trainy)$loss[1] 3.335224$acc[1] 0.8455# Confusion matrixpred <- model %>%   predict_classes(trainx)table(Predicted=pred, Actual=data$train$y[1:2000,])         ActualPredicted   0   1   2   3   4   5   6   7   8   9        0 182   2   8   2   9   4   1   2  10   5        1   1 176   3   5   6   5   2   3   4   7        2   1   0 167   4   3   4   3   2   0   1        3   0   0   0 157   2   1   1   2   1   0        4   2   1   5   6 167   4   2   1   0   0        5   2   0   4   4   3 149   3   4   4   3        6   1   1   3   6   5   2 173   5   0   0        7   3   2   4   2   4   3   9 166   0   1        8  10   1   7   1   6   4   2   2 173   5        9   0   8   2   8   9   7  11  12  11 181

Here, we can see that the loss and accuracy values for the training data are 3.335 and 0.846, respectively. The confusion matrix ...

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