KDAriane

h1. Score

h2. Synopsis

@score@ computes the validation values from a decision file: AUC and the points of the curve; recall, precision and Fscore for each class and their average.

h2. Input format

Each lines has three fields, separated by a tab char:

# The string description of the object, whose first field is the true class

# the decision value for the first class (1), preceeded with a ':'

# the decision value for Class 2, preceeded with a ':'

etc.

h2. Example

<pre>

$ cat score-test.txt

1 5 7 8 12 15 18 22 24 27 30 32 34 36           :11.561 :46.2681

2 5 7 11 13 16 18 22 23 27 30 32 35 38          :0      :850.127

...

$ score score-test.txt

<?xml version="1.0" encoding="UTF-8" standalone="no" ?>

<root>

<roc>

<point x="0" y="0"/>

<point x="0.166667" y="0.533333"/>

<point x="0.166667" y="0.6"/>

<point x="0.166667" y="0.666667"/>

<point x="0.25" y="0.666667"/>

<point x="0.25" y="0.733333"/>

<point x="0.333333" y="0.733333"/>

<point x="0.416667" y="0.733333"/>

<point x="0.416667" y="0.8"/>

<point x="0.416667" y="0.866667"/>

<point x="0.416667" y="0.933333"/>

<point x="0.5" y="0.933333"/>

<point x="0.583333" y="0.933333"/>

<point x="1" y="1"/>

<auc>78.0556</auc>

</roc>

<score>70.3704</score>

<class index="1">

<precision>73.3333</precision>

<recall>73.3333</recall>

<fscore>73.3333</fscore>

<decision class="1">11</decision>

<decision class="1">4</decision>

</class>

<class index="2">

<precision>66.6667</precision>

<recall>66.6667</recall>

<fscore>66.6667</fscore>

<decision class="2">4</decision>

<decision class="2">8</decision>

</class>

<average>

<precision>70</precision>

<recall>70</recall>

<fscore>70</fscore>

</average>

</root>

</pre>

h2. C++ code

The code is avalaible below (score.tgz). Just extract and make, the binary is in the @dist/Release/GNU-Linux-x86@ folder.

h2. Explanations

A short introduction to the evaluation of the supervised classification is given below, in french. The interested reader can also refer to "ROC Graphs: Notes and Practical Considerations for Researchers":http://binf.gmu.edu/mmasso/ROC101.pdf