Binary classification with strongly unbalanced classes
Oct 30, 2017 · Binary classification with strongly unbalanced classes Ask Question Asked 9 years, 2 months ago Modified 5 years, 5 months ago
machine learning - Binary classification: does it make a difference …
Jun 11, 2020 · 4 I'd like to build a binary classification model and I recall reading somewhere that the choice of the labels could have an impact depending on the algorithm. So the two …
Softmax vs Sigmoid function in Logistic classifier?
Sep 6, 2016 · Adding to all the previous answers - I would like to mention the fact that any multi-class classification problem can be reduced to multiple binary classification problems using …
Neural Network: For Binary Classification use 1 or 2 output neurons?
Assume I want to do binary classification (something belongs to class A or class B). There are some possibilities to do this in the output layer of a neural network: Use 1 output node. Output …
Calibration curve of XGBoost for binary classification
Jul 17, 2019 · I'm working on a binary classification problem, with imbalanced classes (10:1). Since for binary classification, the objective function of XGBoost is 'binary:logistic', the …
classification - What is the difference between a multiclass and a ...
Jun 26, 2023 · I suspect the difference is that in multi-class problems the classes are mutually exclusive, whereas for multi-label problems each label represents a different classification …
Should I use a categorical cross-entropy or binary cross-entropy …
However, is binary cross-entropy only for predictions with only one class? If I were to use a categorical cross-entropy loss, which is typically found in most libraries (like TensorFlow), …
In binary classification, in what specific case should I use accuracy ...
May 23, 2018 · When selecting models in binary classification, there are a couple of most often used metrics, such as accuracy, AUROC, F1 score, logloss and Brier score. I understand what …
machine learning - Probability of class in binary classification ...
I have a binary classification task with classes 0 and 1 and the classes are unbalanced (class 1: ~8%). Data is in the range of ~10k samples and #features may vary but around 50-100.
Probability Calibration for Highly Imbalanced Binary Classification
Dec 22, 2022 · 5 I am working on a binary classification problem on a highly imbalanced dataset (1:100) where model probabilities are important for the use case and need to be well …