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Looking for other opinions on approach to classification problem
2019 Community Moderator Electionwhat is buyer classification problem?Classification when one class is otherApproach to Text Classification ProblemBayesian combination of multi-dimensional experts?What methods to create singular content classification from inconsistent inbound info?Why is spam detection a classification problem and not a class modelling problemSelecting ML algorithm for music compositionClassification of keystrokesPearson's Coefficient for classification problemBest approach for classification problem where examples most belong to one set
$begingroup$
I'm looking to implement an "opt-out" filter for my company. The input is short, text-message style messages. A few examples of opt-out messages are:
- "remove me from your list"
- "remove from list"
- "please unsubscribe from list"
- etc.
All other messages are "good", and should not be removed.
My thoughts on approaches:
I was thinking of using a Bayesian classifier here, but not really knowing the solution space (or having much of a background in ML), want to be sure I'm not wasting time on a sub-optimal solution.
I'm fine with not having the most cutting-edge solution, but want to be sure I'm not missing an approach that might be equally as straightforward but more effective.
classification naive-bayes-classifier
asked 14 hours ago
wheresmycookiewheresmycookie
1164
$endgroup$
add a comment |
$begingroup$
I'm looking to implement an "opt-out" filter for my company. The input is short, text-message style messages. A few examples of opt-out messages are:
- "remove me from your list"
- "remove from list"
- "please unsubscribe from list"
- etc.
All other messages are "good", and should not be removed.
My thoughts on approaches:
I was thinking of using a Bayesian classifier here, but not really knowing the solution space (or having much of a background in ML), want to be sure I'm not wasting time on a sub-optimal solution.
I'm fine with not having the most cutting-edge solution, but want to be sure I'm not missing an approach that might be equally as straightforward but more effective.
classification naive-bayes-classifier
asked 14 hours ago
wheresmycookiewheresmycookie
1164
$endgroup$
add a comment |
$begingroup$
I'm looking to implement an "opt-out" filter for my company. The input is short, text-message style messages. A few examples of opt-out messages are:
- "remove me from your list"
- "remove from list"
- "please unsubscribe from list"
- etc.
All other messages are "good", and should not be removed.
My thoughts on approaches:
I was thinking of using a Bayesian classifier here, but not really knowing the solution space (or having much of a background in ML), want to be sure I'm not wasting time on a sub-optimal solution.
I'm fine with not having the most cutting-edge solution, but want to be sure I'm not missing an approach that might be equally as straightforward but more effective.
classification naive-bayes-classifier
asked 14 hours ago
wheresmycookiewheresmycookie
1164
$endgroup$
I'm looking to implement an "opt-out" filter for my company. The input is short, text-message style messages. A few examples of opt-out messages are:
- "remove me from your list"
- "remove from list"
- "please unsubscribe from list"
- etc.
All other messages are "good", and should not be removed.
My thoughts on approaches:
I was thinking of using a Bayesian classifier here, but not really knowing the solution space (or having much of a background in ML), want to be sure I'm not wasting time on a sub-optimal solution.
I'm fine with not having the most cutting-edge solution, but want to be sure I'm not missing an approach that might be equally as straightforward but more effective.
classification naive-bayes-classifier
classification naive-bayes-classifier
asked 14 hours ago
wheresmycookiewheresmycookie
1164
asked 14 hours ago
wheresmycookiewheresmycookie
1164
asked 14 hours ago
wheresmycookiewheresmycookie
1164
asked 14 hours ago
wheresmycookiewheresmycookie
1164
asked 14 hours ago
wheresmycookiewheresmycookie
1164
1164
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
You should use text classification techniques. The most basic one is multinomial naive Bayes classifier with tf-idf features. for this method, take a look at this:
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
If you don’t get enough accuracy (or maybe precision, recall or f-score), you could test more complex techniques e.g. using deep LSTM networks with word embedding. For this method, take a look at this:
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
answered 10 hours ago
pythinkerpythinker
5431211
$endgroup$
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
You should use text classification techniques. The most basic one is multinomial naive Bayes classifier with tf-idf features. for this method, take a look at this:
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
If you don’t get enough accuracy (or maybe precision, recall or f-score), you could test more complex techniques e.g. using deep LSTM networks with word embedding. For this method, take a look at this:
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
answered 10 hours ago
pythinkerpythinker
5431211
$endgroup$
add a comment |
$begingroup$
You should use text classification techniques. The most basic one is multinomial naive Bayes classifier with tf-idf features. for this method, take a look at this:
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
If you don’t get enough accuracy (or maybe precision, recall or f-score), you could test more complex techniques e.g. using deep LSTM networks with word embedding. For this method, take a look at this:
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
answered 10 hours ago
pythinkerpythinker
5431211
$endgroup$
add a comment |
$begingroup$
You should use text classification techniques. The most basic one is multinomial naive Bayes classifier with tf-idf features. for this method, take a look at this:
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
If you don’t get enough accuracy (or maybe precision, recall or f-score), you could test more complex techniques e.g. using deep LSTM networks with word embedding. For this method, take a look at this:
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
answered 10 hours ago
pythinkerpythinker
5431211
$endgroup$
You should use text classification techniques. The most basic one is multinomial naive Bayes classifier with tf-idf features. for this method, take a look at this:
https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
If you don’t get enough accuracy (or maybe precision, recall or f-score), you could test more complex techniques e.g. using deep LSTM networks with word embedding. For this method, take a look at this:
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
answered 10 hours ago
pythinkerpythinker
5431211
answered 10 hours ago
pythinkerpythinker
5431211
answered 10 hours ago
pythinkerpythinker
5431211
answered 10 hours ago
pythinkerpythinker
5431211
5431211
add a comment |
add a comment |
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