MinSizeKmeans
kmodes
| MinSizeKmeans | kmodes | |
|---|---|---|
| 1 | 2 | |
| 80 | 1,223 | |
| - | - | |
| 0.0 | 4.2 | |
| about 3 years ago | 17 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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MinSizeKmeans
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Preliminary Evidence that Retail Trades can be Identified and Counted on the Tape
Sure so basically I scraped the volume from the SEC report figure depicting 'Buy' volume by measuring pixels between ticks on the y axis. I also downloaded all regular session trades for the dates in that figure and after some rounds of data cleaning (ie one hot encoding trade condition data) I ran the trades from the first half through an implementation of kmeans clustering with minimum cluster size constraints set to cluster the trades weighted by volume into 2 groups with minimum weight of the volume scraped from the candle from the SEC report. This clustering takes a long time to run so I've only managed to process that first bar.
kmodes
- kmodes, Python package for categorical clustering releases version 0.12.0. Now with sample weighting and Python 3.10 support.
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How much of data science is lying?
They were probably looking for K-modes
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