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1 vote
2 answers
804 views

How to analyse results of classification for time series + sliding windows

Here is my context: I have a time series composed of only 1 features. I want to be able to classify between two classes. To get more information out of these data, I am using a sliding time windows. ...
Adrien's user avatar
  • 19
1 vote
2 answers
944 views

Cross Validation for Time Series Classification (Not Forecasting!)

Is it possible to use regular k-fold cross validation where the folds contain entire time series in time series classification? I'm asking because most sources discussing cross validation with time ...
perceptronEnthusiast420's user avatar
5 votes
0 answers
690 views

Predict churn in a range of time after observation window is finished

I'm building a churn model. Each user's historic data (observation window) is a constant period, but each observation window contains different dates. For example the next figure: Let's say, that the ...
Amit S's user avatar
  • 77
1 vote
0 answers
350 views

what is it an activity window in churn model?

I know that in a churn model many times you define an observation window (historic data) and a performance window (also dependent window, or response window). I have read an article that the authors (...
Amit S's user avatar
  • 77
1 vote
0 answers
748 views

How to make predictions on sliding window?

I need help understanding how to construct sliding windows as well as how to perform final prediction. Any help is appreciated! I have a dataset from sensing data with multiple features aggregated ...
Subi's user avatar
  • 11
2 votes
2 answers
1k views

Supervised learning: setting labels on sliding windows of sensor data

Suppose that I have a set of accelerometer data collected with one sensor and one label for each measured data point. These labels describe different states of my system e.g., $state_A, state_B, ...
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