Linked Questions

15
votes
4answers
15k views

Macro- or micro-average for imbalanced class problems

The question of whether to use macro- or micro-averages when the data is imbalanced comes up all the time. Some googling shows that many bloggers tend to say that micro-average is the preferred way ...
1
vote
2answers
2k 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. ...
3
votes
2answers
2k views

True positives and true negatives, F1 score: multi class classification

I have 4 classes for an application of classification of animal kingdom: 1 --> invertibrates; 2 --> vertibrates; 3--> mammal; 4 ---> ambhibian. Given a mixture of images the objective is to identify ...
5
votes
1answer
889 views

Multiclass classification on imbalanced dataset : Accuracy or micro F1 or macro F1

I have a multiclass classification problem. Further, an instance can be assigned to exactly one class. My dataset is highly imbalanced. I know that accuracy is not a good metric to use in this case ...
1
vote
2answers
1k views

Which method should be considered to evaluate the imbalanced multi-class classification?

I am working on multiclass-imbalanced data. My dependent variable is highly skewed. ...
0
votes
1answer
583 views

Difference of sklearns accuracy_score() to the commonly accepted Accuracy metric

I am trying to evaluate the accuracy of a multiclass classification setting and I'm wondering why the sklearn implementation of the accuracy score deviates from the commenly agreed on accuracy score: $...
0
votes
1answer
425 views

Choice of f1 score for highly imbalanced dataset?

I am confused whether to use f1 score with 'micro' average or 'macro' average for better evaluation. Given my dataset is highly imbalanced(600:100000)
7
votes
3answers
209 views

Understanding Classifier performance on text data

I am working on a multi-label text classification problem(Total target labels 90). The data distribution has a long tail and class imbalance and around 1900k records. Currently, I am working on a ...
1
vote
0answers
20 views

Difference between MAP@K for recommendations, MAP from Precision Recall Curves and Macro-Precision

I have been using the 3 metrics independently for a while now, but trying to figure out if they are actually 3 separate things (with similar-looking definitions/names) or there is some underlying ...