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Questions tagged [overfitting]

For questions related to the concept of overfitting in machine learning, which can be loosely defined as the gap between the performance on the training set and the performance on the test set.

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7 votes
2 answers
6k views

How can I handle overfitting in reinforcement learning problems?

So this is my current result (loss and score per episode) of my RL model in a simple two players game: I use DQN with CNN as a policy and target networks. I train my model using Adam optimizer and ...
malioboro's user avatar
  • 2,819
14 votes
4 answers
4k views

What is the "dropout" technique?

What purpose does the "dropout" method serve and how does it improve the overall performance of the neural network?
kenorb's user avatar
  • 10.5k
7 votes
1 answer
439 views

What is the best measure for detecting overfitting?

I wanted to ask about the methodology of testing the ML models against overfitting. Please note that I don't mean any overfitting reducing methods like regularisation, just a measure to judge whether ...
GKozinski's user avatar
  • 1,260
5 votes
1 answer
498 views

How can I avoid overfitting when doing parameter tuning?

I very often applied a grid search to tune the parameters of my supervised model. I have the feeling that parameter tuning will eventually (very often) lead to overfitting? Is this crazy to say? Is ...
jennifer ruurs's user avatar
5 votes
1 answer
796 views

Are deep learning models more prone to overfitting than machine learning ones?

In my opinion, deep learning algorithms and models (that is, multi-layer neural networks) are more sensitive to overfitting than machine learning algorithms and models (such as the SVM, random forest, ...
jennifer ruurs's user avatar
5 votes
1 answer
193 views

Is running more epochs really a direct cause of overfitting?

I've seen some comments in online articles/tutorials or Stack Overflow questions which suggest that increasing the number of epochs can result in overfitting. But my intuition tells me that there ...
Alexander Soare's user avatar
1 vote
1 answer
138 views

Interpretation of a good overfitting score

As shown below, my deep neural network is overfitting : where the blue lines is the metrics obtained with training set and red lines with validation set Is there anything I can infer from the fact ...
Astariul's user avatar
  • 371
0 votes
1 answer
92 views

What are possible ways to combat overfitting or improve the test accuracy in my case?

I have asked a question here, and one of the comments suggested that this is a case of severe overfitting. I made a neural network, which uses residual boosting (which is done via a KNN), and I am ...
jr123456jr987654321's user avatar
0 votes
2 answers
94 views

Could I just choose the other (non-predicted) class when the accuracy is low?

I have a binary classification problem. My neural network is getting between 10% and 45% accuracy on the validation set and 80% on the training set. Now, if I have a 10% accuracy and I just take the ...
jr123456jr987654321's user avatar