Questions tagged [binary-classification]

Question 1

When building a binary classification model using a neural network, you have two options for outputs: output a single number from 0 to 1 using sigmoid activation, or output a probability distribution ...

Question 2

Consider a population of fixed size where each member can in one of two classes. Although new elements will NEVER be added to the population over time, some of the existing elements may change value. ...

Question 3

I have a piece of software where N% of users convert to a paid plan after a 2 week free trial. I train the model (random forest) to use the first 2 days of usage data to predict whether the user ...

Question 4

I am working on a content-based recommendation system. I am planning to frame this as a binary classification problem (1 = click/0 = not click). And I was looking for paper/readings on feature ...

Question 5

I have two strings that represent two institutions. For instance, a1="University of Milan" a2="University Milan" or ...

Question 6

I'm training a classifier on the DAIGT dataset. The objective is to differentiate human from AI text and so this is a binary classification problem. As a baseline before I move onto an LLM classifier, ...

Question 7

beginner of ML here. Can anyone tell me if it is advisable to apply ML models, specifically binary classification and using Pycaret on a dataset with 69 columns and 226 rows? it has columns for ...

Question 8

I am trying to reimplement a paper in PyTorch that was originally implemented in Lua. The model is a GAN, and I have a specific question with discriminator. The discriminator is trying to detect ...

Question 9

I am working on a highly imbalanced fraud detection dataset (class 0:284315 instances, class 1: 492 instances) and trying to implement random undersampling correctly during cross-validation in Orange. ...

Question 10

I am using a small data set for an ML project and the data set consists of about 550 samples. I am doing binary classification. I was told to take laplacian of the data set and then do eigenvalue and ...

Question 11

I'm trying to implement a binary classification model using tensorflow keras and stumbled over problem that I cannot grasp. My model shall classify images of houses in the two classes of "old/...

Question 12

I am a beginner self-learning machine learning and I'm currently dealing with a binary classification problem. I made a binary classifier with a basic neural network and I did some experiments with ...

Question 13

This is a very general question so lets take a very general example: imagine a CNN model that distinguishes between dogs and cats facial features images. we have two kinds of training data set: one ...

Question 14

I am comparing 5 third party classification models on a subset of results (specifically, false positives I am examining to find a common cause). The five models all output values between 0 and 1 but ...

Question 15

I've run both SVM with Polynomial kernel with a degree of 3 and Logistic Regression with transformed features by PolynomialFeatures with the same degree of 3 on the default scikit-learn's Moons ...

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Questions tagged [binary-classification]

Scalar versus 2-element output for binary classification models

Population of fixed size that evolves over time

Is it valid to resolve A/B tests earlier using usage data?

What are some good resources to read about recommendation systems to help build your own?

If my binary classifier results in a negative outcome, is it right to try again with another classifier which has the same FPR but higher recall?

Much higher scoring metrics with classification_report than cross_validate

Binary classification on small dataset

Binary Classifier's Output and Lua Torch

how to properly implement Random Undersampling during Cross-Validation in Orange

What does taking laplacian of a data set means?

Using keras metrics BinaryCrossentropy for a binary model

Confidence levels and error rates in binary classification models

Is it better to train a CNN model with bad images or good images when the testing data will be in bad quality?

Correct way to compare results of binary classifiers with different sensitivities

Why does SVM have a worse decision boundary than Logistic Regression?

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