This repo has an example of an annotated SciKit Learn example of ML Classification using the Clustering Algo Meanshift
Uses bitstamp BTC/USD historic value from api.bitcoincharts.com
The target of this code is to find resistance lines in trading chart data (OHLC)
The codebase is simple, this is a fork of the forex_algotrading project, please check the "sources" section of this readme for info about the original repo
Run:
./setup.sh
This will install everything and it will also automatically starts an HTTP server
To execute the "data crunching" and "chart annotating" job, use run.sh:
./run.sh
To build and execute python via docker-compose, run:
./recompose.sh
Run a server, for example the python SimpleHTTPServer via:
./serve.sh
Project forked from https://github.com/jonromero/forex_algotrading
Currently it doesn't draws the direction yet - TODO: 'feature', not yet in the backlog)
Images sometimes are better than many words :D
"recent" image
shrinkage around the 9k-12k area
If you want to use it "as it is" you will need to configure the AWS S3 credentials as that's the current way I'm saving/publishing the results. You want to comment all that code if you just to run it locally instead of automated inside docker.
You probably want also to tune quantile for the MeanShift clusterization to match the current price action. A range in between x and x should do that (The target is to find a quantile value that generates min 3-4 to max 8-10 clusters)
Enjoy!
@makevoid



