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amoeba
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This answer follows up on another threadmy answer whichin Bias and variance in leave-one-out vs K-fold cross validation that discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

Repeating the experiment from the previous thread (see here), we now introduce a certain ratio of outliers in the data set. In particular:

Performing the simulation as previously and plotting the resulting average MSE and variance of the MSE gives results very similar to experimentExperiment 2 of the Bengio and GrandvaletBengio & Grandvalet 2004 paper.

enter image description here

(see the linked paper for explanation of the last figure)

Quoting Yves Grandvalet's answerYves Grandvalet's answer on the other thread:

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

Repeating the experiment from the previous thread, we now introduce a certain ratio of outliers in the data set. In particular:

Performing the simulation as previously and plotting the resulting average MSE and variance of the MSE gives results very similar to experiment 2 of the Bengio and Grandvalet paper.

enter image description here

Quoting Yves Grandvalet's answer on the other thread:

This answer follows up on my answer in Bias and variance in leave-one-out vs K-fold cross validation that discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

Repeating the experiment from the previous thread (see here), we now introduce a certain ratio of outliers in the data set. In particular:

Performing the simulation as previously and plotting the resulting average MSE and variance of the MSE gives results very similar to Experiment 2 of the Bengio & Grandvalet 2004 paper.

enter image description here

(see the linked paper for explanation of the last figure)

Quoting Yves Grandvalet's answer on the other thread:

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amoeba
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#[EDIT - TL: DR]

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

#[EDIT - TL: DR]

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

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This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an inherently unstable model"unstable model".

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an inherently unstable model.

This answer follows up on another thread which discusses why LOOCV does not always lead to higher variance. Following a similar approach, I will attempt to highlight a case where LOOCV does lead to higher variance in the presence of outliers and an "unstable model".

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