feat: add continues prediction to OutPutconvertion #740
Assignees
Labels
Comments
lars-reimann
pushed a commit
that referenced
this issue
Jul 19, 2024
## [0.27.0](v0.26.0...v0.27.0) (2024-07-19) ### Features * join ([#870](#870)) ([5764441](5764441)), closes [#745](#745) * activation function for forward layer ([#891](#891)) ([5b5bb3f](5b5bb3f)), closes [#889](#889) * add `ImageDataset.split` ([#846](#846)) ([3878751](3878751)), closes [#831](#831) * add FunctionalTableTransformer ([#901](#901)) ([37905be](37905be)), closes [#858](#858) * add InvalidFitDataError ([#824](#824)) ([487854c](487854c)), closes [#655](#655) * add KNearestNeighborsImputer ([#864](#864)) ([fcdfecf](fcdfecf)), closes [#743](#743) * add moving average plot ([#836](#836)) ([abcf68a](abcf68a)) * add RobustScaler ([#874](#874)) ([62320a3](62320a3)), closes [#650](#650) [#873](#873) * add SequentialTableTransformer ([#893](#893)) ([e93299f](e93299f)), closes [#802](#802) * add temporal operations ([#832](#832)) ([06eab77](06eab77)) * added 'histogram_2d' in TablePlotter ([#903](#903)) ([4e65ba9](4e65ba9)), closes [#869](#869) [#798](#798) * added from_str_to_temporal and continues prediction ([#767](#767)) ([35f468a](35f468a)), closes [#806](#806) [#765](#765) [#740](#740) [#773](#773) * added GRU layer ([#845](#845)) ([d33cb5d](d33cb5d)) * Adds Dropout Layer ([#868](#868)) ([a76f0a1](a76f0a1)), closes [#848](#848) * dark mode for plots ([#911](#911)) ([5447551](5447551)), closes [#798](#798) * easily create a baseline model ([#811](#811)) ([8e1b995](8e1b995)), closes [#710](#710) * get first cell with value other than `None` ([#904](#904)) ([5a0cdb3](5a0cdb3)), closes [#799](#799) * hyperparameter optimization for fnn models ([#897](#897)) ([c1f66e5](c1f66e5)), closes [#861](#861) * implement violin plots ([#900](#900)) ([9f5992a](9f5992a)), closes [#867](#867) * plot decision tree ([#876](#876)) ([d3f81dc](d3f81dc)), closes [#856](#856) * prediction no longer takes a time series dataset only table ([#838](#838)) ([762e5c2](762e5c2)), closes [#837](#837) * raise if `remove_colums` is called with unknown column by default ([#852](#852)) ([8f78163](8f78163)), closes [#807](#807) * regularization strength for logistic classifier ([#866](#866)) ([9f74e92](9f74e92)), closes [#750](#750) * reorders parameters of RangeScaler and makes them keyword-only ([#847](#847)) ([2b82db7](2b82db7)), closes [#809](#809) * replace seaborn with matplotlib for box_plot ([#863](#863)) ([4ef078e](4ef078e)), closes [#805](#805) [#849](#849) * replaced seaborn with matplotlib for correlation_heatmap ([#850](#850)) ([d4680d4](d4680d4)), closes [#800](#800) [#849](#849) ### Bug Fixes * **deps:** bump urllib3 from 2.2.1 to 2.2.2 ([#842](#842)) ([b81bcd6](b81bcd6)), closes [#3122](https://github.com/Safe-DS/Library/issues/3122) [#3363](https://github.com/Safe-DS/Library/issues/3363) [#3122](https://github.com/Safe-DS/Library/issues/3122) [#3363](https://github.com/Safe-DS/Library/issues/3363) [#3406](https://github.com/Safe-DS/Library/issues/3406) [#3398](https://github.com/Safe-DS/Library/issues/3398) [#3399](https://github.com/Safe-DS/Library/issues/3399) [#3396](https://github.com/Safe-DS/Library/issues/3396) [#3394](https://github.com/Safe-DS/Library/issues/3394) [#3391](https://github.com/Safe-DS/Library/issues/3391) [#3316](https://github.com/Safe-DS/Library/issues/3316) [#3387](https://github.com/Safe-DS/Library/issues/3387) [#3386](https://github.com/Safe-DS/Library/issues/3386) * labels of correlation heatmap ([#894](#894)) ([a88a609](a88a609)), closes [#871](#871) * make multi-processing in baseline models more consistent ([#909](#909)) ([fa24560](fa24560)), closes [#907](#907) ### Performance Improvements * improved performance in various methods in `Image` and `ImageList` ([#879](#879)) ([134e7d8](134e7d8))
|
🎉 This issue has been resolved in version 0.27.0 🎉 The release is available on:
Your semantic-release bot 📦🚀 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Is your feature request related to a problem?
Right now the outputsize of a TimeSeries in a nn Model is always 1, because we predict the value in forecast horizon steps.
Desired solution
I want to add the ability that the user forecasts until the forecast horizon, so the outputsize will be the forecast horizon, as all steps until the forecast horizon, will be also forecasted.
Possible alternatives (optional)
No response
Screenshots (optional)
No response
Additional Context (optional)
No response
The text was updated successfully, but these errors were encountered: