Comments (1)
HI Astor,
Our test set has one chunk per covariate and they are predicted independently. For the datasets with a small number of covariates, you could probably run evaluation with the original test set, but with many covariates it is intractable, as the number of series to predict will be (number of covariates) x (number of temporal chunks).
Nate
from llmtime.
Related Issues (20)
- Prediction length for Monash benchmark HOT 4
- Description not found for p_extra HOT 1
- Autoformer experiments HOT 2
- The example does not support openai after the version is upgraded HOT 1
- How to run Llama 70B? HOT 1
- How were the normalized scores aggregated? HOT 2
- Question about the continuous likelihood. HOT 2
- Question about the generate_predictions() function HOT 1
- Fine-tuning with tabular data HOT 5
- import darts.models error
- add suggestions for usage requirements for openAI HOT 2
- Basic usage without an LLM key? HOT 6
- Reproducibility of LLM-Time results on Informer datasets
- nvm.
- NLL function is missing for GPT HOT 3
- ImportError: cannot import name 'load_dataset' from 'datasets' (unknown location) from monash.py HOT 1
- Missing LLaMa from experiments HOT 2
- how to use local csv data to test? HOT 1
- how to get future forecasting points?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from llmtime.