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fix bug in DBSCAN, update doc

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This commit is contained in:
Robert Caulk
2022-08-04 17:00:59 +02:00
parent 29225e4baf
commit fe1b8515a8
2 changed files with 33 additions and 11 deletions
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docs/freqai.md
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@@ -539,11 +539,19 @@ The user can tell FreqAI to use DBSCAN to cluster training data and remove outli
parameter `DBSCAN_outlier_pct` allows the user to indicate the percent of expected outliers to be removed during each training
(typically set below 0.05). Higher value increases confidence in the model predictions but reduces the entry frequency.
The FreqAI DBSCAN wrapper performs an interative solution to solving the `eps` hyper parameter. `eps` controls the fraction of
The FreqAI DBSCAN wrapper performs an iterative solution to solving the `eps` hyper parameter. `eps` controls the fraction of
training data considered to be an outlier - thus the iterative solution finds the exact value associated with the user designated
`DBSCAN_outlier_pct`. This iterative solution is performed once per training. FreqAI stores the `eps` to be used when DBSCAN
is again called to determine if incoming prediction candles are outliers.
```json
"freqai": {
"feature_parameters" : {
"DBSCAN_outlier_pct": 0.05
}
}
```
### Stratifying the data
The user can stratify the training/testing data using: