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Hello Community,
I have been searching and trying different types of datasheets. Some of them gave me a reasonable ratio of error, but others are really high. For instance this file gave me 112% of error, so the model is useless for this example. ProductName(1).csv
The text was updated successfully, but these errors were encountered:
@maxlelyonais I know it has been a while since you posted this question, but I wanted to share a few thoughts regarding Prophet and predictions:
You can transform numbers using either the natural logarithm or logarithm base 10. This method has consistently improved Prophet's performance with the data I've worked with.
I ran Prophet on your data and achieved a Mean Absolute Percentage Error (MAPE) of 112% using the base model with the raw values you provided. However, after converting the raw target values to natural logs, I improved the MAPE to 93%.
Hello Community,
I have been searching and trying different types of datasheets. Some of them gave me a reasonable ratio of error, but others are really high. For instance this file gave me 112% of error, so the model is useless for this example.
ProductName(1).csv
The text was updated successfully, but these errors were encountered: