Commit e71ddd79 authored by Marina Bertolino's avatar Marina Bertolino

DOC: update classification receipe for the unsupervised classifier and contingency table

parent 42938d20
......@@ -4,10 +4,10 @@ Classification
Pixel based classification
--------------------------
Orfeo ToolBox ships with a set of application to perform supervised
pixel-based image classification. This framework allows to learn from
multiple images, and using several machine learning method such as
SVM, Bayes, KNN, Random Forests, Artificial Neural Network, and
Orfeo ToolBox ships with a set of application to perform supervised or
unsupervised pixel-based image classification. This framework allows
to learn from multiple images, and using several machine learning method
such as SVM, Bayes, KNN, Random Forests, Artificial Neural Network, and
others...(see application help of ``TrainImagesClassifier`` and
``TrainVectorClassifier`` for further details about all the available
classifiers). Here is an overview of the complete workflow:
......@@ -347,8 +347,9 @@ using the ``TrainVectorClassifier`` application.
-feat band_0 band_1 band_2 band_3 band_4 band_5 band_6
The ``-classifier`` parameter allows to choose which machine learning
model algorithm to train. Please refer to the
``TrainVectorClassifier`` application reference documentation.
model algorithm to train. You have the possibility to do the unsupervised
classification,for it, you must to choose the Shark kmeans classifier.
Please refer to the ``TrainVectorClassifier`` application reference documentation.
In case of multiple samples files, you can add them to the ``-io.vd``
parameter (see `Working with several images`_ section).
......@@ -409,6 +410,11 @@ class too, based on the
`ConfusionMatrixCalculator <http://www.orfeo-toolbox.org/doxygen-current/classotb_1_1ConfusionMatrixCalculator.html>`_
class.
If you have made an unsupervised classification, it must be specified
to the ``ConputeConfusionMatrix`` application. In this case, a contingency table
have to be create rather than a confusion matrix. For further details,
see ``format`` parameter in the application help of *ConputeConfusionMatrix*.
::
otbcli_ComputeConfusionMatrix -in labeled_image.tif
......
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