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**First, this project's ambition is just impressive. My biggest impressions lie on two points:**
_**Innovative and relevant approach:**_ Most college students like us would not think of developing …
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- [x] Introduction - scope 0.5-1 page
- look into reviews
- broad overview into the field
- mention nature methods "method of the year 2020"
- define axis: targeted/high-resolution vs unbiased…
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To enhance the predictive performance of our models (Linear Regression, Random Forest, Gradient Boosting, LSTM, ARIMA, SARIMA), we need to explore and implement various feature engineering strategies.…
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The team aims to train a classifier to predict the genre of a song given the musical data. The data they used include a 300GB unlabeled dataset as well as the labeled Allmusic Top Genre Dataset.
Th…
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related to #943
943 and related discussion is on how to handle outliers. AFAICS, the main approach for outlier detection and handling for ARMA and similar models are based intervention models, and …
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get the following error
shape mismatch: value array of shape (53,1) could not be broadcast to indexing result of shape (53,).
I'm using numpy 1.13.1 version and statsmodels 0.8.0
My code is:
imp…
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Would you like an implementation of Natural Cubic Spline interpolation for missing data?
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The various projection methods currently implemented don't seem to handle incomplete triangles out of the box. It would be very useful if they did.
E.g. I'm looking at an example where I have some…
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Check how much of your feature space has been imputed by triage. This would give a little bit more of context to the already available plot showing the sparsity of the test matrix.
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- PyTorch-Forecasting version: 0.8.2
- PyTorch version: 1.7.1
- Python version: 3.8
- Operating System: Ubuntu 20.04
If I understand it correctly, then the `TimeSeriesDataSet` fills missing valu…