query: Neural network model having high validation loss shows higher accuracy in test data during cross validation process
positive_passages.docid: 145878
positive_passages.text: Overfitting on the loss graph, but not the accuracy graph
negative_passages.docid: 114625
negative_passages.text: Model selection and cross-validation: The right way
negative_passages.docid: 126373
negative_passages.text: Can we use MLE to estimate Neural Network weights?
negative_passages.docid: 84407
negative_passages.text: How to judge if a supervised machine learning model is overfitting or not?
negative_passages.docid: 60956
negative_passages.text: Difference of Activation Functions in Neural Networks in general
negative_passages.docid: 77118
negative_passages.text: What did my neural network just learn? What features does it care about and why?
negative_passages.docid: 86032
negative_passages.text: How to determine the confidence of a neural network prediction?
negative_passages.docid: 48226
negative_passages.text: How to adjust the hyperparameters of MLP classifier to get more perfect performance
negative_passages.docid: 107224
negative_passages.text: Why you shouldn't upsample before cross validation
negative_passages.docid: 141640
negative_passages.text: Sklearn - Choosing the right model for supervised learning/classification task
negative_passages.docid: 135800
negative_passages.text: Validation of Models with Different Scale Data
negative_passages.docid: 25409
negative_passages.text: Why does k-fold cross validation generate an MSE estimator that has higher bias, but lower variance then leave-one-out cross-validation?
negative_passages.docid: 13041
negative_passages.text: Using neuralnet with caret train and adjusting the parameters
negative_passages.docid: 60749
negative_passages.text: What could be the reasons that making validation loss jumping up and down?
negative_passages.docid: 62891
negative_passages.text: How to construct a cross-entropy loss for general regression targets?
negative_passages.docid: 54989
negative_passages.text: Why is binary cross entropy (or log loss) used in autoencoders for non-binary data
negative_passages.docid: 38075
negative_passages.text: What is the trade-off between batch size and number of iterations to train a neural network?