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Questions tagged [multilabel-classification]

Multilabel classification assigns to each sample a set of target labels. This can be thought as predicting properties of a data-point that are not mutually exclusive, such as topics that are relevant for a document. A text might be about any of religion, politics, finance or education at the same time or none of these.

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Categorizing Customer Emails

I am working on a project for a company which needs to categorize customer e-mails regarding loans and insurance. The e-mails are labeled uniquely from set of 13 category labels. The number of records ...
Pranay Mathur's user avatar
3 votes
2 answers
4k views

What is the formula to calculate the precision, recall, f-measure with macro, micro, none for multi-label classification in sklearn metrics?

I am working in the problem of multi-label classification tasks. But I would not able to understand the formula for calculating the precision, recall, and f-measure with macro, micro, and none. ...
Ashok Kumar Jayaraman's user avatar
3 votes
1 answer
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Transform multi-label problem to multi-class problem

What are the downsides of modelling a multi-label problem as a multi-class problem with a single classifier? Let my clarify what I mean. There at least two ways that one multi-label problem can be ...
Outcast's user avatar
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2 votes
3 answers
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How to apply supervised machine learning when the target label depends on multiple input rows?

The problem is a multi-label classification problem. Now, I know how to train and classify using single row with several attributes. For example, if the dataset looks like the first table from the ...
AtanuCSE's user avatar
  • 121
13 votes
6 answers
35k views

How to use sklearn train_test_split to stratify data for multi-label classification?

I am attempting to mirror a machine learning program by Ahmed Besbes, but scaled up for multi-label classification. It seems that any attempt to stratify the data returns the following error: ...
Michael Joy's user avatar
5 votes
3 answers
25k views

Multi-class neural net always predicting 1 class after optimization

During training, the neural net settles into a place where it always predicts 1 of the 5 classes. My train and test sets are distributed as such: ...
jamis's user avatar
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3 votes
1 answer
2k views

Activation method and Loss function for multilabel multiclass classification

I am using CNN for Sentence Classification code by Yoonkim. This is used for text classification. I noticed that he uses softmax layer and negative log likelihood error. This is optimal for single ...
Hima Varsha's user avatar
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3 votes
1 answer
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How to correctly perform data sampling for train/test split in multi-label dataset?

Problem statement I have a text multi-label classification dataset, and I've found a problem with the dataset sampling. I'm facing two different strategies. The first one consists in preprocessing ...
Alber8295's user avatar
  • 155
2 votes
1 answer
2k views

Balancing XGboost still skews towards the majority class

I have unbalanced dataset for multiclass classification and I tried to use the class weights option in XGboost and the classifier still tends to favor the majority class. I am not sure if I need to ...
Swap's user avatar
  • 41
1 vote
1 answer
409 views

Multi-label classification for text messages (convert text to numeric vector)

Given a dataset of messages which are labeled with 20 features, I want to predict the value of each feature for a new message. Dataset example: ...
Oscar Martinez's user avatar
1 vote
2 answers
5k views

How to feed data to multi-output Keras model from a single TFRecords file

I know how to feed data to a multi-output Keras model using numpy arrays for the training data. However, I have all my data in a single TFRecords file comprising several feature columns: an image, ...
magomar's user avatar
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1 vote
1 answer
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How to trust the labels generated using ML models?

I have a dataset of patient records. But I do not know whether he is +ve for a cancer or not. So, I do not have the labels in my dataset. Now I can run a machine learning models like clustering to ...
The Great's user avatar
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0 votes
1 answer
310 views

Transform multi-class problem to multi-label problem

I found this question but I need an answer to the other direction. Example: Let's say we want to predict if a person with a certain profile wants to buy product A and/or B. So we have 2 binary classes ...
LineBreak's user avatar
0 votes
1 answer
1k views

LSTM Multi-class classification for large number of classes

I want to build a model that classifies 473 classes -product categories-, but I'm facing a problem with loss not decreasing. Data I have almost 3,000 data points for each class -473 classes- (data ...
Khaled's user avatar
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