Questions tagged [concept-drift]

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Datasets for demonstrating data/model/concept drift

Are there any well-known datasets that are useful for illustrating the concept of data and/or model/concept drift? I can create my own out of, say, MNIST (by e.g. removing digits and adding them in ...
Jennie Lan Chien's user avatar
4 votes
3 answers
412 views

What techniques are used to analyze data drift?

I've created a model that has recently started suffering from drift. I believe the drift is due to changes in the dataset but I don't know how to show that quantitatively. What techniques are ...
Connor's user avatar
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How to visualize a data drift?

I want to show that my data distribution changes between data windows. Is it enough to visualize the mean and variance for every window? Is there any other solution? thank you
Imen F's user avatar
  • 21
1 vote
1 answer
146 views

What are the advantages of model drift vs concept drift in online learning?

I have asked this question here but I'm also posting it here to get a better insight: https://stats.stackexchange.com/questions/602282/what-are-the-advantages-of-model-drift-vs-concept-drift-in-online-...
Ash's user avatar
  • 129
2 votes
1 answer
250 views

What is the differenc between Real concept drift, virtual concept drift and feature drift

As far as I know, the real concept drift is caused by changes in the decision boundary while virtual drift occurs because of changes in data distribution. Some researchers mention that virtual drift ...
Imen F's user avatar
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3 votes
1 answer
1k views

What is the difference between Covariate Shift, Label Shift, Concept Shift, Concept Drift, and Prior Probability Shift?

As a beginner in MLOps, I was overwhelmed by some confusing definitions. As far as I understand, when we have a classifier or regressor with y = f(X) function: <...
Mohsen Mahmoodzadeh's user avatar
2 votes
0 answers
199 views

Detecting Data Drift in Audio Data

For a give set of audio files collected from an industrial process via a microphone, I have extracted suitable features and fed them into a neural network for training a binary classifier as depicted ...
TwinPenguins's user avatar
  • 4,219
2 votes
1 answer
73 views

Dealing with historic data drift

I'm trying to predict a continuous target in an industrial context. The problem I'm facing is that the some of the predictors have changed over time, for example the pressure in the machine was ...
David So's user avatar
3 votes
2 answers
266 views

Is it possible to detect drift with real time predictions?

I have been reading up on detecting data drift and concept drift, I have found this library but it seems all the methods here detect concept drift and take input as if the prediction was correct or ...
iiphiizy's user avatar
3 votes
2 answers
148 views

Predictive modeling when output affects future input

Assume I have a model which predicts the outcome of the number of icecreams sold in a store. The model is trained on data for the last 5 years while keeping the last year as a validation set and has ...
CutePoison's user avatar