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Peter Babič 9 years ago
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@ -10,7 +10,7 @@ yaourt -S robocode libsvm
# Usage
```
Generate the data required for SVM classification and show the accuracy
of the generated SVM model. If coordinates are supported, one visual battle
of the generated SVM model. If coordinates are provided, one visual battle
is shown to support the prediction.
USAGE: robocode-svm ACTION
@ -30,7 +30,7 @@ The robots on test are **sample.Corners** (starting in center) and **sample.Trac
The SVM type used is **C-SVC** (multi-class classification), with the **radial basis** kernel. The *cost* parameter C is **10** and the *sigma* parameter is **2**. You can find more details about these at [libsvm home](https://github.com/cjlin1/libsvm).
## 2D visualisation
When the third parameter (initial gun orientation) of the roaming robot is omitted, we can generate *sample* visualisation of the result of this classification. Our experiments were indicating, that this parameter has low (about 2%) significance on the output of the battle.
When the third parameter (initial gun orientation) of the roaming robot is omitted, we can generate *sample* visualisation of the result of this classification. Our experiments were indicating, that this parameter has low (about 2%) significance on the outcome of the battle.
![2D visualisation](https://github.com/delmadord/robocode_svm/blob/master/extras/visualize2D.png)

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