# Tag Info

### What is the difference between Multiclass and Multilabel Problem

Multiclass classification means a classification task with more than two classes; e.g., classify a set of images of fruits which may be oranges, apples, or pears. Multiclass classification makes the ...
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### Multilabel classification metrics on scikit

The subset accuracy is indeed a harsh metric. To get a sense of how good or bad 0.29 is, some idea: look at how many labels you have an average for each sample look at the inter-annotator agreement, ...
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### What is the difference between Multiclass and Multilabel Problem

To complement the other answers, here are some figures. One row = the expected output for one sample. Multiclass One column = one class (one-hot encoding) Multilabel One column = one class You ...
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### How to apply Softmax as Activation function in multi-layer Perceptron in scikit-learn?

The MLPClassifier can be used for "multiclass classification", "binary classification" and "multilabel classification". So the output layer is decided based on type of Y : Multiclass: The outmost ...
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### Better performance using Random Forest one-Vs-All than Random Forest multiclass?

I had exactly the same question as you, and was a bit sad to find out no answers were posted on your topic... That said, I found this paper : One-Vs-All Binarization Technique in the Context of ...
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Accepted

### Error while performing multiclass classification using Gridsearch CV

Accuracy might look tempting but not a good metric in general. In multilabel classification, for each class we'll have f1 score, ...
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### How to compute accuracy for multi class classification problem and how is accuracy equal to weighted precision?

I've got a wonderful solution and a perfect understandable solution for this problem as I was looking for same from this Question You can calculate and store accuracy with: ...
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Accepted

### Imbalanced multiclass classification with many classes

There is no real answer to your question, because it really depends on what you are trying to archive, i.e. is your goal to get a very high classification accuracy or is it rather data exploration? ...
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Accepted

### Optimize classification rule in multinomial logistic regression

The question is ill-posed. If you are trying to optimise some function of specificity and sensitivity (other than accuracy) for a logistic regression model by altering the classification threshold, ...
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Accepted

### Suggestions needed about classifier fusion

There are several approaches to combine classifiers, and in your case, what you are doing is one of them. Also, it is reasonable to expect an improvement in the combined classifier compared to either ...
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