Row 97413
Content Data
This page contains data entry 97413 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
Wow, that is probably the most advanced machine learning research I have ever read. What they are doing is very interesting, and admittedly, much of the paper went way over my head. My only question/concern would be overfitting with the very specific lags. I understand why lagging the impact of factors is important and found the negative lags to be an interesting place to further research, but I would be curious to see the results when pooling multiple factors together in regard to lags. Similar factors should have similar lags and by pooling them (essentially batch uploading) you may prevent overfitting with very minor impacts on performance.
| Field | Value |
|---|---|
| text | Wow, that is probably the most advanced machine learning research I have ever read. What they are doing is very interesting, and admittedly, much of the paper went way over my head. My only question/concern would be overfitting with the very specific lags. I understand why lagging the impact of factors is important and found the negative lags to be an interesting place to further research, but I would be curious to see the results when pooling multiple factors together in regard to lags. Similar… |
| label | r/machinelearning |
| dataType | comment |
| communityName | r/MachineLearning |
| datetime | 2024-05-25 |
| username_encoded | Z0FBQUFBQm5Lak12dWxDMW5FWEJIdDh0UktDWl93azZEWkM5aURzTGxYMWdxLXVxNkFVVmJuU1ZrekpjSzExcjNiQkdxWXRUS2Q5SHB6NEZhRG45YVpuZVRTVDc5dzhIckE9PQ== |
| url_encoded | Z0FBQUFBQm5LalBCLXhVcE9VUFQwb0V1dlhCNW1tM1VfZFdNV1lwbGI3UTV1d20wMkVYWFB1S2c4RXdDa19WZDlBbFBwV2hrMWVjeTF5d01kWnRFWG9Ua3hMX0FqQmN5M010bm5WdjVpQWdGMU1QM1poazN2ekwzc0phYk9QTnJ6dXp2ZzgyWTZnVDJKbmpLaDduamRWcXRLclg2dU0wRG15a3A2cklGV29ManFlNHJ4SXU3aVd0Q0lDQjZCbk5JODFabHV0MEc0MnZLQllDdXFBMVc3RzJRYnp1NklOMmc1Zz09 |
Raw Record
{
"text": "Wow, that is probably the most advanced machine learning research I have ever read. What they are doing is very interesting, and admittedly, much of the paper went way over my head. My only question/concern would be overfitting with the very specific lags. I understand why lagging the impact of factors is important and found the negative lags to be an interesting place to further research, but I would be curious to see the results when pooling multiple factors together in regard to lags. Similar factors should have similar lags and by pooling them (essentially batch uploading) you may prevent overfitting with very minor impacts on performance.",
"label": "r/machinelearning",
"dataType": "comment",
"communityName": "r/MachineLearning",
"datetime": "2024-05-25",
"username_encoded": "Z0FBQUFBQm5Lak12dWxDMW5FWEJIdDh0UktDWl93azZEWkM5aURzTGxYMWdxLXVxNkFVVmJuU1ZrekpjSzExcjNiQkdxWXRUS2Q5SHB6NEZhRG45YVpuZVRTVDc5dzhIckE9PQ==",
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}
Entry Information
- Entry ID: 97413
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000