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don't train or untrain empty word hashes #132
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Original file line number | Diff line number | Diff line change |
---|---|---|
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@@ -73,7 +73,9 @@ def train(category, text) | |
|
||
@backend.update_category_training_count(category, 1) | ||
@backend.update_total_trainings(1) | ||
Hasher.word_hash(text, @language, @enable_stemmer).each do |word, count| | ||
word_hash = Hasher.word_hash(text, @language, @enable_stemmer) | ||
return if word_hash.length == 0 | ||
word_hash.each do |word, count| | ||
@backend.update_category_word_frequency(category, word, count) | ||
@backend.update_category_word_count(category, count) | ||
@backend.update_total_words(count) | ||
|
@@ -91,7 +93,9 @@ def untrain(category, text) | |
category = CategoryNamer.prepare_name(category) | ||
@backend.update_category_training_count(category, -1) | ||
@backend.update_total_trainings(-1) | ||
Hasher.word_hash(text, @language, @enable_stemmer).each do |word, count| | ||
word_hash = Hasher.word_hash(text, @language, @enable_stemmer) | ||
return if word_hash.length == 0 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Move this up in the method as well. |
||
word_hash.each do |word, count| | ||
next if @backend.total_words < 0 | ||
orig = @backend.category_word_frequency(category, word) || 0 | ||
@backend.update_category_word_frequency(category, word, -count) | ||
|
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I would make it the very first thing to happen in the method. This current change is essentially changing nothing significantly.
update_category_training_count
andupdate_total_trainings
are still being called, hence causing undesired stats changes. Also, if the@auto_categorize
is set totrue
, it might add a new category without any trainings in it.There was a problem hiding this comment.
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Do you want to preempt
add_category
or justupdate_category_training_count
andupdate_total_trainings
?There was a problem hiding this comment.
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I would make it the very first thing in the method, even before calling
CategoryNamer
. This way, if the training has to be skipped, it does not make any changes in the data-structure state in any circumstances.