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| author | Toni Uhlig <matzeton@googlemail.com> | 2022-10-10 15:40:25 +0200 |
|---|---|---|
| committer | Toni Uhlig <matzeton@googlemail.com> | 2022-10-10 16:44:12 +0200 |
| commit | 20fc74f52742e5d512723d4f5fe314626e4a92f3 (patch) | |
| tree | 70fa1fd99a1d4cf08e827f3f4030abbe30832840 /examples/README.md | |
| parent | 2ede930eec0aceb292687351ed520784c060380c (diff) | |
Improved py-machine-learning example.
Signed-off-by: Toni Uhlig <matzeton@googlemail.com>
Diffstat (limited to 'examples/README.md')
| -rw-r--r-- | examples/README.md | 7 |
1 files changed, 7 insertions, 0 deletions
diff --git a/examples/README.md b/examples/README.md index 4a5b9b339..b378f26ae 100644 --- a/examples/README.md +++ b/examples/README.md @@ -42,6 +42,13 @@ Prints prettyfied information about flow events. Use sklearn together with CSVs created with **c-analysed** to train and predict DPI detections. +Try it with: `./examples/py-machine-learning/sklearn-ml.py --csv ./ndpi-analysed.csv --proto-class tls.youtube --proto-class tls.github --proto-class tls.spotify --proto-class tls.facebook --proto-class tls.instagram --proto-class tls.doh_dot --proto-class quic --proto-class icmp` + +This way you should get 9 different classification classes. +You may notice that some classes e.g. TLS protocol classifications may have a higher false-negative rate. + +Unfortunately, I can not provide any datasets due to some privacy concerns. + ## py-flow-dashboard A realtime web based graph using Plotly/Dash. |