Multi-label classification where multiple target labels might be assigned to each instance.
Questions tagged [multilabel]
180 questions
114
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7 answers
What is the difference between a multiclass and a multilabel problem?
What is the difference between a multiclass problem and a multilabel problem?
Learner
- 4,507
43
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3 answers
What are the measure for accuracy of multilabel data?
Consider a scenario where you are provided with KnownLabel Matrix and PredictedLabel matrix. I would like to measure the goodness of the PredictedLabel matrix against the KnownLabel Matrix. But the challenge here is that KnownLabel Matrix have few…
Learner
- 4,507
31
votes
3 answers
Would a Random Forest with multiple outputs be possible/practical?
Random Forests (RFs) is a competitive data modeling/mining method. An RF model has one output -- the output/prediction variable. The naive approach to modeling multiple outputs with RFs would be to construct an RF for each output variable. So we…
redcalx
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29
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4 answers
Multilabel classification metrics on scikit
I am trying to build a multi-label classifier so as to assign topics to existing documents using scikit I am processing my documents passing them through the TfidfVectorizer the labels through the MultiLabelBinarizer and created a…
mobius
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27
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2 answers
How to use scikit-learn's cross validation functions on multi-label classifiers
I'm testing different classifiers on a data set where there are 5 classes and each instance can belong to one or more of these classes, so I'm using scikit-learn's multi-label classifiers, specifically sklearn.multiclass.OneVsRestClassifier . Now I…
chippies
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13
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2 answers
How to apply neural networks on multi-label classification problems?
Description: Let the problem domain be document classification where there exists a set of feature vectors, each belonging to 1 or more classes. For example, a document doc_1 might belong to Sports and English categories. Question: Using neural…
IssamLaradji
- 379
11
votes
3 answers
Multilabel logistic regression
Is there a way to use logistic regression to classify multi-labeled data? By multi-labeled, I mean data that can belong to multiple categories simultaneously. I would like to use this approach to classify some biological data.
user721975
- 925
10
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2 answers
Neural network for multi label classification with large number of classes outputs only zero
I am training a neural network for multilabel classification, with a large number of classes (1000). Which means more than one output can be active for every input. On an average, I have two classes active per output frame. On training with a cross…
Yakku
- 111
10
votes
1 answer
Micro vs weighted F1 score
In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account? The main upside of choosing macro is that one gets a sense of effectiveness on small classes. Assuming that…
Franck Dernoncourt
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9
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1 answer
Multi-label or multi-class...or both?
I'm having a hard time getting the difference between multi-class and multi-label classification with CNNs. My understanding is that if I want to classify different breeds of dogs, that is a multi-label classification as I have the same class of…
amel
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9
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2 answers
What measures should one use to evaluate a multilabel classification?
There are several evaluation measures for multilabel classification. In the mlr package tutorial you can see some of them: http://mlr-org.github.io/mlr-tutorial/devel/html/measures/index.html and even more in this paper…
PhilippPro
- 1,174
9
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1 answer
What is the difference between a multi-label and a multi-class classification?
What is the difference between multi-label classification and multiclass classfication. Speficially, what is the difference between a label and a class? Please provide a clear example. "Multiclass classification should not be confused with…
7
votes
2 answers
What is the statistical model for a multi-label problem?
In a setting with a binary $y$ like dog/cat, a reasonable statistical model is to posit that the probability parameter $p$ of a $\text{Binomial}(1, 0)$ distribution is some function $f$ of features $X$ . This leads to many common machine learning…
Dave
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7
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2 answers
Can target encoding be performed on a multi-label classification problem?
Is there a way to perform target encoding on multi label (closed set) problems, obviously target encoding is used on multi-class problems all the time, but i'm wondering if it works for multi label problems as well? and if there are any specialized…
7
votes
1 answer
Why does keras binary_crossentropy loss function return wrong values?
Binary cross entropy for multi-label classification can be defined by the following loss function: $$-\frac{1}{N}\sum_{i=1}^N [y_i \log(\hat{y}_i)+(1-y_i) \log(1-\hat{y}_i)]$$ Why does keras binary_crossentropy loss function return different values?…
Dmitry
- 181