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+Torch metrics package
+====================
+
+This package provides utility functions to evaluate your machine learning models.
+
+#### Disclaimer:
+
+Use at your own risk. The code is not extensively tested, therefore it might contain bugs. 
+If you find any, please let me know and I will try to fix it.
+
+#### Installation:
+
+```sh
+git clone https://github.com/hpenedones/metrics.git
+cd metrics
+luarocks make
+```
+
+#### Receiver Operator Curves (ROC)
+
+Used to evalute performance of binary classifiers, and their trade-offs in terms of false-positive and false-negative rates.
+
+```lua
+require 'torch'
+metrics = require 'metrics'
+gfx = require 'gfx.js'
+
+resp = torch.DoubleTensor { -0.9, -0.8, -0.8, -0.5, -0.1, 0.0, 0.2, 0.2, 0.51, 0.74, 0.89}
+labels = torch.IntTensor  {   -1,   -1,    1,   -1,   -1,   1,   1,  -1,   -1,    1,    1}
+
+roc_points, thresholds = metrics.roc.points(resp, labels)
+area = metrics.roc.area(roc_points)
+
+print(roc_points)
+print(thresholds)
+print(area)
+
+gfx.chart(roc_points)
+
+```
+
+![](https://raw.githubusercontent.com/hpenedones/metrics/master/img/roc1.png)
+
+#### Confusion matrix (TODO)
+
+Used to evaluate performance of multi-class classifiers.