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forecasting

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sktime
Lovkush-A
Lovkush-A commented Aug 13, 2021

Describe the bug
If you load arrow_head data with default split settings, the resulting dataframe has indices that repeat. this is because there is a concatenation of train and test data

To Reproduce

from sktime.datasets import load_arrow_head
X, y = load_arrow_head(return_X_y=True)
X.index.values

Output:

array([  0,   1,   2,   3,   4,   5,   6,   7,   8,
gluon-ts
fawolfmann
fawolfmann commented Oct 26, 2020

Is your feature request related to a current problem? Please describe.
In order to create an outlier detection with Prophet, i need the full dataframe that's return Prophet

Describe proposed solution
Remove the hardcoded ["yhat"] from Prophet.predict add a variable asking to return just yhat or all the predictions: 'yhat_lower', 'yhat_upper', etc..
https://unit8co.github.io/d

HariWu1995
HariWu1995 commented Jun 3, 2021

Dear team,

I am in stuck when convert very large numpy array to your TSDatasets.
These are what I have tried to fix my issue:

  • when building time-series, I used tensorflow.keras.preprocessing.timeseries_dataset_from_array. After this step, the memory is still fine
  • I concatenate all batch data into numpy array, this step produces problem so I use numpy memmap to avoi
flow-forecast

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