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Feature Engineering a Recency feature

I think an exponential decay or RBF feature would map close dates towards 1.0, and distant dates to smaller values (approaching zero in the limit). In particular, consider this formulation: $\mathrm{...
MuhammedYunus's user avatar
0 votes

How to deal with over confident model?

From your description it's a little difficult to understand what you mean by "overconfident". It seems strange that your model might be very confident in predicting data that are completely ...
healthydata's user avatar
1 vote

Should I standardise time series data for deep learning classification?

Most time series classification algorithms do not take the time index as input, so there's no point standardising the time index. The description for some algorithms will mention a time index, but ...
Lynn's user avatar
  • 1,307
3 votes
Accepted

Train/test split of data, stratified based on label, but ensuring no athletes are In both train/test sets

I think you may use the concept of groups as implemented in scikit-learn. In GroupShuffleSplit you may set a column of groups. Then the split won't happen across groups. Either a group as a whole is ...
Avi T's user avatar
  • 56
1 vote

Unordered Set Classification Problem

Typical setup for this would be to one hot encode each unordered set, so we have $M$ boolean indicator variables. And then we might train on cosine distance, to predict each label.
J_H's user avatar
  • 1,110
0 votes
Accepted

Data binning for interval data

regression This is a regression problem, not a classification problem. So model it with a regressor. Your loss function can choose to discretize each prediction before scoring it, if that's what you ...
J_H's user avatar
  • 1,110

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