Linked Questions

19
votes
11answers
18k views

Why is logistic regression called a machine learning algorithm?

If I understood correctly, in a machine learning algorithm, the model has to learn from its experience, i.e when the model gives the wrong prediction for the new cases, it must adapt to the new ...
35
votes
4answers
29k views

When should I balance classes in a training data set?

I had an online course, where I learned, that unbalanced classes in the training data might lead to problems, because classification algorithms go for the majority rule, as it gives good results if ...
9
votes
3answers
14k views

Logistic regression: maximizing true positives - false positives

I have a logistic regression model (fit via glmnet in R with elastic net regularization), and I would like to maximize the difference between true positives and false positives. In order to do this, ...
14
votes
5answers
2k views

Philosophical question on logistic regression: why isn't the optimal threshold value trained?

Usually in logistic regression, we fit a model and get some predictions on the training set. We then cross-validate on those training predictions (something like here) and decide the optimal threshold ...
16
votes
3answers
14k views

hinge loss vs logistic loss advantages and disadvantages/limitations

Hinge loss can be defined using $\text{max}(0, 1-y_i\mathbf{w}^T\mathbf{x}_i)$ and the log loss can be defined as $\text{log}(1 + \exp(-y_i\mathbf{w}^T\mathbf{x}_i))$ I have the following questions: ...
13
votes
2answers
6k views

When is logistic regression suitable?

I'm currently teaching myself how to do classification, and specifically I'm looking at three methods: support vector machines, neural networks, and logistic regression. What I am trying to understand ...
7
votes
3answers
3k views

regression for binary classification

Given a binary classification problem, is there any inherent difference (or advantage) to using a classifier (say a logistic regression) and a regression, where the classes are denoted by 0 and 1 (or ...
13
votes
2answers
7k views

Assessing logistic regression models

This question arises from my actual confusion about how to decide if a logistic model is good enough. I have models that use the state of pairs individual-project two years after they are formed as a ...
13
votes
2answers
8k views

How do you predict a response category given an ordinal logistic regression model?

I want to predict a health problem. I have 3 outcome categories that are ordered: 'normal', 'mild', and 'severe'. I wish to predict this from two predictor variables, a test result (a continuous, ...
7
votes
3answers
4k views

Logistic regression: maximum likelihood vs misclassification

Traditionally the fitting of the logistic regression function is explained using maximum likelihood. Could one fit the logistic regression function as well based on either least-squares or based on ...
5
votes
4answers
2k views

Loss vs. Classification Accuracy in applied problems

In practical problems, where we want to for instance predict if a subject has a certain disease or not, we usually take classification accuracy as a measure which has the straightforward ...
6
votes
2answers
8k views

Adjusting probability threshold for sklearn's logistic regression model

I am a 10th grade student working on a binary classification problem and I have decided to use the logistic regression model from Scikit-Learn. I am looking to predict patient adherence given the time ...
5
votes
2answers
4k views

Why is Logistic Regression mentioned by many sources as useful in predicting stock prices?

My understanding of Logistic Regression is that it is actually a classifier, hence used for predicting either a categorical outcome (ie. binary or an outcome with specific labels) as opposed to a ...
2
votes
2answers
6k views

Confusion about cv.glm in R

R's document says that delta is the raw cross-validation estimate of prediction error, which i think is prediction error rate in the situation of logistic regression. However, when i try to calculate ...
5
votes
1answer
6k views

XGBClassifier and XGBRegressor

I am a newbie to Xgboost and I would like to use it for regression, in particular, car prices prediction. I started following a tutorial on XGboost which uses XGBClassifier and objective= 'binary:...

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