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Same dictionary different results #10
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One thing I can think of is the random initialization in the IsolationForest model which can cause some differences in results. Other than that, this shouldn't be happening. If the data changes the next time you run it, then it makes sense. |
I see different results when loading from the saved Downloading Data
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Is there some sort of time decay in the score factor? If I run it now vs an hour from now using the same dictionary I'll get different Symbols, the Symbols which are the same have different scores. What's going on?
python detection_engine.py --top_n 25 --min_volume 5000 --data_granularity_minutes 60 --history_to_use 14 --is_load_from_dictionary 1 --data_dictionary_path 'dictionaries/data_dict.npy' --is_save_dictionary 0 --is_test 0 --future_bars 0 --output_format JSON
VS
[latest_date] => 2020-09-03 15:30:00-04:00
[Symbol] => SHLO
[Anomaly Score] => -0.089904823370707
[Today Volume] => 191.8M
[Average Volume 5d] => 4.4M
[Average Volume 20d] => 1.6M
[Volatility 5bars] => 0.039062185261644
[Volatility 20bars] => 0.16062981405984
This was number 4 the first time:
[latest_date] => 2020-09-03 15:30:00-04:00
[Symbol] => SBPH
[Anomaly Score] => -0.064138750572796
[Today Volume] => 178.03K
[Average Volume 5d] => 129.7K
[Average Volume 20d] => 102.2K
[Volatility 5bars] => 0.0067650775893322
[Volatility 20bars] => 0.090846754019149
7th the second time:
[latest_date] => 2020-09-03 15:30:00-04:00
[Symbol] => SBPH
[Anomaly Score] => -0.054286909962896
[Today Volume] => 178.03K
[Average Volume 5d] => 129.7K
[Average Volume 20d] => 102.2K
[Volatility 5bars] => 0.0067650775893322
[Volatility 20bars] => 0.090846754019149
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