Questions tagged [bias-variance-tradeoff]
For questions related to the bias-variance tradeoff, which is an important issue in machine learning.
8
questions
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1answer
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What is the bias-variance trade-off in reinforcement learning?
I am watching DeepMind's video lecture series on reinforcement learning, and when I was watching the video of model-free RL, the instructor said the Monte Carlo methods have less bias than temporal-...
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0answers
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Do the variance and bias belong to the policy or value functions?
Recently, I read many papers on variance and bias. But I am still confused by the two notions, the variance or bias belongs to who? Policy or value? If the variance or bias is large or low, what ...
3
votes
1answer
94 views
How does Monte Carlo have high variance?
I was going through David Silver's lecture on reinforcement learning (lecture 4). At 51:22 he says that Monte Carlo (MC) methods have high variance and zero bias. I understand the zero bias part. It ...
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votes
1answer
92 views
Why does reinforcement learning using a non-linear function approximator diverge when using strongly correlated data as input?
While reading the DQN paper, I found that randomly selecting and learning samples reduced divergence in RL using a non-linear function approximator (e.g a neural network).
So why does Reinforcement ...
2
votes
1answer
44 views
How can I determine the bias and variance of a random forrest?
On this website https://scikit-learn.org/stable/modules/learning_curve.html, the authors are speaking about variance and bias and they give a simple example of how works in a linear model.
How can I ...
4
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2answers
75 views
Why is having low variance important in offline policy evaluation of reinforcement learning?
Intuitively, I understand that having an unbiased estimate of a policy is important because being biased just means that our estimate is distant from the truth value.
However, I don't understand ...
2
votes
0answers
65 views
How is the bias caused by a max pooling layer overcome?
I have constructed a CNN that utilizes max-pooling layers. I have found with these layers that, should I remove them, my network performs ideally with every output and gradient at each layer having a ...
3
votes
2answers
170 views
What makes a machine learning algorithm a low variance one or a high variance one?
Some examples of low-variance machine learning algorithms include linear regression, linear discriminant analysis, and logistic regression.
Examples of high-variance machine learning algorithms ...
