Binary classification with strongly unbalanced classes
Oct 30, 2017 · Binary classification with strongly unbalanced classes Ask Question Asked 9 years, 1 month ago Modified 5 years, 4 months ago
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 …
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 …
optimizing auc vs logloss in binary classification problems
Nov 22, 2022 · I am performing a binary classification task where the outcome probability is fair low (around 3 per cent). I am trying to decide whether to optimize by AUC or log-loss. As much …
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 …
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), …
what is the best activation function for binary classification?
Apr 3, 2023 · If you mean at the very end (it seems like you do), it is determined by your data. Since you want to do a binary classification of real vs spoof, you pick sigmoid. Softmax is a …
Can the mean squared error be used for classification?
Jan 5, 2020 · Technically you can, but the MSE function is non-convex for binary classification. Thus, if a binary classification model is trained with MSE Cost function, it is not guaranteed to …
Intuitive explanation of conformal prediction - Cross Validated
Mar 9, 2023 · Binary classification. Conformal prediction for binary classification is best thought of as giving well-calibrated probability scores such that when all cases whose probabilities are …