Questions tagged [f1score]

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3answers
141 views

Too high performances on a classification problem

I have a .json file as dataset of the type: and I am working on a classification problem in which I have to predict 4 classes, which are rhe semantic. I have worked through the problem, and after ...
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4answers
131 views

Is an $F_1$ score of 0.1 always bad?

I'm currently building a model to predict early mortgage delinquency (60+ days delinquent within 2 years of origination) for loans originating in 2018Q1. I will eventually train out-of-time (on loans ...
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1answer
36 views

Model to choose with Cross Validation or not?

I made different tests on an imbalanced dataset and got these results: Model 1 = train test validation split + Cross Validation(cv=10) --> f1'micro' 0,95 Model 2 = train test split + smote method ...
1
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1answer
29 views

how print f1-score with scikit´s accuracy_score or accuracy of confusion_matrix?

I would like to print the f1-score. I got confused about the wording f1-accuracy score and accuracy score. What is the difference of these 2 scikit-learn metrics and how can I print the f1-score out ...
1
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1answer
46 views

Multiclass Classification and log_loss

I hope I can make this clear with few lines of code/explanation. I've a 16K list of texts, labelled over 30 different classes that were ran through different classifiers; my Prediction and the Ground ...
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2answers
251 views

Accuracy is lower than f1-score for imbalanced data

For a binary classification, I have a dataset with 55% negative label and 45% positive labels. The results of the classifier shows that the accuracy is lower than the f1-score. Does that mean that the ...
1
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1answer
39 views

Selecting threshold for F1 Score

When selecting a probability threshold to maximize the F1 score prior to deploying a model (based on the precision-recall curve), should the threshold be selected based on the training or holdout ...
0
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1answer
16 views

How to calculate the evaluation metrics (i.e., F1 score) in leave one subject out cv when a subject belongs to single class only

I have dataset of 10 subjects. the dataset has 4 classess. 0,1,2 and 3. The distribution of classes are not same. For example subject 1 does not have 1,2 and 3. It belongs to zeros class. currently ...
1
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1answer
26 views

Is it conscientious to use a threshold for a model output in order to play on the recall and precision?

I have just finished reading an article about the F1 score, recall and precision. Everything was clear except the fact that the author, in his example (see https://towardsdatascience.com/beyond-...
3
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1answer
21 views

F1 score graph skewed

The following code ...
4
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1answer
182 views

Balanced Accuracy vs. F1 Score

I've read plenty of online posts with clear explanations about the difference between accuracy and F1 score in a binary classification context. However, when I came across the concept of balanced ...
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0answers
139 views

How can I calculate the F1 score using Mask RCNN?

I customized the "https://github.com/matterport/Mask_RCNN.git" repository to train with my own data set, for object detection, ignoring the mask segmentation part. Now I am evaluating my results, I ...
0
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1answer
72 views

Confusion matrix of UNET image sgemenation model

I have used Unet model for image segmentation. I have used RGB images and corresponding image masks and at output i got corresponding region of interest. Now i want to find confusion matrix of this ...
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0answers
24 views

Measuring performance of classifiers with different/extra classes

Disclosure - This is also on cross-validated, but has no comments or answers. Then I found this forum and thought it may be best suited here. I'm not sure where to post this, or how best to explain, ...
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0answers
156 views

Calculating the F score of Object Detection of Mask RCNN

I am using Detectron2 Mask RCNN for an object detection problem. The images consist of cells that are very close to each other. I can not use mAP as a performance measure since the annotations are a ...
8
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3answers
2k views

Can the F1 score be equal to zero?

As it is mentioned in the F1 score Wikipedia, 'F1 score reaches its best value at 1 (perfect precision and recall) and worst at 0'. What is the worst condition that was mentioned? Even if we ...
-1
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1answer
59 views

What is evaluation metric for two sets? [closed]

I've two sets one is ground truth and other is output of my machine learning models. Assume my groundtruth set is A={1,2,3,4,5} and output of machine learning model is B={3,4,5,6,7,8}. One way I can ...
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0answers
16 views

Monotonicity of Jaccard and Dice in multilabel datasets

I understand that Jaccard and Dice follow a monotonic relation on binary datasets because the two are related as $J = {S \over {(2 - S)}}$, and I guess this would be the case when micro-average is ...
0
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1answer
78 views

Different definitions of Macro F1 score, which one is used in Scikit-learn?

In this article Macro F1 and Macro F1 two different definitions of the F1 used in the literature are demonstrated. The first F1 score is computed such as: F1 scores are computed for each class ...
3
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1answer
31 views

Multiclass imbalanced classification

I have a dataset with the target variable having 3 classes. Value counts of Target variable are as follows: ...
1
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1answer
493 views

Macro F1 result higher than accuracy for imbalanced dataset

In one of the research papers on fake news detection, the authors collected a fake news binary dataset (fake vs. real news) consists of 16,817 real articles and <...
0
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0answers
17 views

Can a binary classification model have lower accuracy, but higher F1-score [duplicate]

I am just reviewing some results where someone compared results of two binary classification models and the results state that model M1 achieved higher accuracy ...
2
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1answer
305 views

How to correctly calculate average F1 score, precision and recall of a Named Entity Recognition system?

My Named Entity Recognition (NER) pipeline built with Apache uimaFIT and DKPro recognizes named entities (called datatypes for now) in texts (e.g. persons, locations, organizations and many more). I ...
4
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1answer
43 views

Visualizing F-score differences in information extraction

I have several corpora and NLP systems (including a few merge ensembles of output of these systems combined in unions and intersections) with which I have extracted the annotation span sets {(begin, ...
2
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1answer
639 views

Is it possible to make F1_Score differentiable and use it directly as a Loss function?

One of the metrics that is widely used in binary classification is the F1 score: $F_1 = 2\cdot \frac{recall \cdot precision}{recall+precision}$ The problem of the F1-score is that it is not ...