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Questions tagged [cross-validation]

For questions related to the cross-validation technique used e.g. in machine learning or statistics.

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How can I split the data into training and validation sets such that entries with a certain value are kept together?

I have the following kind of data frame. These are just example: A 1 Normal A 2 Normal A 3 Stress B 1 Normal B 2 Stress B 3 Stress C 1 Normal C 2 Normal C 3 Normal ...
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1answer
42 views

Relationship between training accuracy and validation accuracy

During model training, I noticed various behaviour in between training and validation accuracy. I understand that 'The training set is used to train the model, while the validation set is only used to ...
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3answers
103 views

How do you interpret this learning curve?

Loss is MSE; orange is validation loss, blue training loss. The task is NN regression (18 inputs, 2 outputs), one layer 300 hidden units. Tuning the lr, mom, l2 regularization parameters this is the ...
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3answers
211 views

Is k-fold cross-validation more effective than splitting the dataset into training and test datasets to prevent overfitting?

I want to prevent my model from overfitting. I think that k-fold cross-validation (because it is doing this each time with different datasets) may be more effective than splitting the dataset into ...
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1answer
16 views

Can we say: the more we increase the numbers of cross validation the less likely it is that we overfit?

Based on the answer of my previous question: How can I avoid overfitting when doing parameter tuning? Can we say: the more we increase the numbers K of cross validation the less likely it is that we ...
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1answer
55 views

How to interpret this learning curve plot

Bellow I have a Learning Curve plot How should I interpret this plot for my random forrest algorithm (the second one the most complex one)? Which one is the best?
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1answer
58 views

How should I interpret this validation plot?

Bellow I have a validation plot How should I interpret this validation plot? Is my data underfitting? What else can be seen from this? Which one is the best? What does it mean that the right line is ...
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1answer
50 views

Metrics for evaluating models that output probabilities

I'm aware of metrics like accuracy (correct predictions / total predictions) for models that classify things. However, I'm working on a model that outputs the probability of a datapoint belonging to ...
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2answers
39 views

Ideal score of a model on training and cross validation data

The question is little bit broad, but I could not find any concrete explanation anywhere, hence decided to ask the experts here. I have trained a classifier model for binary classification task. Now ...
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1answer
53 views

Leave One Out Testing

I am currently working with a small dataset of 20x300. Since I have so few datapoints, I was wondering if I could use an approach similar to leave-one-out cross-validation but for testing. Here's ...
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1answer
99 views

Which model is better given their training and validation errors?

Below you have the plots of the training and validation errors for two different models. Both plots show the RMSE values for the validation dataset versus the number of training epochs. It is observed ...
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1answer
13 views

Should I call the error “validation error” or “test error” during cross validation?

I'm using 10-fold cross validation on all models. Here you can see both plots: Since I am using k-fold cross validation, is it okay to name it "validation error vs training error" or "test error vs ...