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### Feature request
I have implemented and tested a feature that trains a time series model - ARIMA and serves it using BentoML's custom runner to make predictions.
### Motivation
I believe it woul…
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**Issue**
I am training a TSMixerModel to forecast multivariate time series. The model performs well overall, but I notice that the training loss is consistently much lower than the validation loss (…
erl61 updated
13 hours ago
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from: @jack-bilby :
> 12: aperm.default(X, c(s.call, s.ans))
> 11: aperm(X, c(s.call, s.ans))
> 10: apply(x, 1, function(y) (sum(is.na(y))/length(y)) > maxNA.fraction)
> 9: which(apply(x, 1, fun…
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Shapley explanation works for the whole prediction set, however sometimes one needs to explain every step in the forecasting. This is a complex issue due to using different approaches - direct or recu…
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Plots like this don't look too great (Italy)
![image](https://user-images.githubusercontent.com/7837158/78340064-5f6c6800-758d-11ea-8dce-10b5e6056bcc.png)
This is happening because the trend for t…
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Currently, Spark ```@pandas_udf``` does not support UDT for both input and output.
We should contribute to Spark to make the following code feasible.
```
df = spark.createDataFrame([Row(id=1, i…
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## Overview
Although Series 4 is the current _de facto_ series of interest, there seem to be some open questions regarding series 3 (S3). For example, it is still unknown which target is hit by se…
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It would be interesting to be able to add bootstrapping functionnality from residuals of a model of the time series, this would help :
1. to compute prediction intervals when the method doesn't su…
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**Issue Title**: Implement Stock Trading Bot using LSTM with `yfinance` and Backtesting
**Description**:
We need to implement a stock trading bot that utilizes Long Short-Term Memory (LSTM) netw…
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# Food Demand Forecasting for Restaurants
**Tier:** 2-Advanced
Food demand forecasting for restaurants is an application built to estimate the food demand that a restaurant is expected to receiv…