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Which models for time series forecasting fedot uses? Can you provide examples? Is there any comparison with competitors? @RepoPilotAssistant please help
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### Short description of current behavior
Important note, I have a 4 months old Mindsdb docker image where everything works perfectly fine. This bug is related to newer versions only.
1. Create …
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Hello! I recently read the article Are Language Models Actually Useful for Time Series Forecasting. I also noticed that your experiments included ablation studies from this paper, which demonstrated t…
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### Description
Amazon Chronos-T5: https://huggingface.co/amazon/chronos-t5-large
IBM Granite: https://huggingface.co/ibm-granite/granite-timeseries-ttm-v1
Lag-Llama: https://huggingface.co/time-…
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# Moving Average (MA) and ARMA Models | Chan`s Jupyter
A Summary of lecture “Time Series Analysis in Python”, via datacamp
[https://goodboychan.github.io/python/datacamp/time_series_analysis/2020/06…
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### What happened + What you expected to happen
Tried fitting AutoMLForecast with a series that has different id_col and getting an error saying "unique_id" not found. Problem is that `id_col` isn't …
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In this, we will convert a time series problem to a supervised machine learning problem to predict driver demand. Exploratory analysis has to be performed on the time series to identify patterns. A re…
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Since structural time series models only require fitting process and observation error variance parameters (unlike ARIMA models, for example), the gradient of the log-likelihood function can be comput…
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## Pain Point
Currently, we have few models capable of time series forecasting and we need more models for the same.
## Proposed Solution
Implement the following models in DFFML:
- [ ] [RN…