<commit_before>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
others...(see application help of ``TrainImagesClassifier`` and
``TrainOGRLayersClassifier`` for further details about all the available
classifiers). Here is an overview of the complete workflow:

1. Compute samples statistics for each image
2. Compute sampling rates for each image (only if more than one input image)
3. Select samples positions for each image
4. Extract samples measurements for each image
5. Compute images statistics
6. Train machine learning model from samples<commit_msg>DOC: Error in application name<commit_after>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
others...(see application help of ``TrainImagesClassifier`` and
``TrainVectorClassifier`` for further details about all the available
classifiers). Here is an overview of the complete workflow:

1. Compute samples statistics for each image
2. Compute sampling rates for each image (only if more than one input image)
3. Select samples positions for each image
4. Extract samples measurements for each image
5. Compute images statistics
6. Train machine learning model from samples
{'fraction_non_alphanumeric': 0.08543577981651376, 'fraction_numerical': 0.006880733944954129, 'mean_word_length': 4.575079872204473, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2487248', 'n_tokens_mistral': 396, 'n_tokens_neox': 374, 'n_words': 227}