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Questions tagged [logistic-regression]

For questions related to Logistic regression in the context of machine learning and AI. Logistic regression is a statistical classification model used for making categorical predictions.

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What is the right formula for weight update rule in Logistic Regression using stochastic gradient descent

Apologies for the lengthy title. My question is about the weight update rule for logistic regression using stochastic gradient descent. I have just started experimenting on Logistic Regression. I ...
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What is meant by "the number of examples is reduced", and why is this the case?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.2. Logistic Regression, the author says the following: 3.2. Logistic ...
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Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
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Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?

I am using raw data set with 4 feature variables (Total Cholesterol, Systolic Blood Pressure, Diastolic Blood Pressure, and Cigraeette count) to do a Binominal Classification (find stroke likelihood) ...
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How to define cost function for custom nonlinear functions?

For logistic regression, the Cost function is defined as: \begin{equation} Cost(h_{\theta}(x)-y) = -ylog(h_{\theta}(x))-(1-y)log(1-h_{\theta}(x)) \end{equation} I now have a nonlinear function \begin{...
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Is it possible to apply entity fixed effects to a firth logit test?

All, Currently working with a large dataset (~1.6 million observations) with a relatively low number of rare events (~600ish). To summarize, I'm looking at the impact of 7 foreign-policy related ...
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Is the loss calculation step in Logistic Regression even needed?

I was reading about Logistic Regression and trying to implement the model from scratch. Maybe I am wrong, but I have noticed that the loss calculation step is meaningless in training a Logistic ...
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Data Imbalance in Contextual Bandit with Thompson Sampling

I'm working with the Online Logistic Regression Algorithm (Algorithm 3) of Chapelle and Li in their paper, "An Empirical Evaluation of Thompson Sampling" (https://papers.nips.cc/paper/2011/...
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How does the distribution of the parameters change in logistic regression?

I have my own data to train a logistic regression model (for a multi-class classification task), and I want to know how the distribution of weight parameters changes after each update with gradient ...
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Is it possible to compute the logical AND and OR with logistic regression?

It's easy to build a perceptron that can compute the logical AND and OR functions of its binary inputs. Logistic regression could be used as a binary classifier. $$z^{(i)} = w^T x^{(i)} + b$$ $$\hat{y}...
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Is the main difference between the logistic regression and the perceptron the activation function they use?

I went through a Stats StackExchange's post about the difference between logistic regression and perceptron, which is too long to get the key point. I'd like to consider the question in terms of the ...
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Given the same features, do logistic regression and neural networks produce the same output?

I have a binary classification problem. I have variables (features) var1, var2, var3, ..., var14. Using these variables (aka features) in a logistic regression, I get their weights. If I use the same ...
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Neural Networks vs Logistic regression

I'm new to Neural Network and would like understand its essential parts and difference from simple logistic regression. Let's take an example of Coffee Roasting prediction (example from Andre NG ...
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In logistic regression, do I try to fit the graph perfectly or mimimize the error in the predicted probabilities?

In linear regression, I train the model so the graph runs best through the data points, so the geometric distance between f(x) and $y^i$ is minimized. Now, is it correct that in logistic regression I ...
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How do we interpret the images of weights in logistic regression

The following images are a) The weights of a logistic regression model trained on MNIST. b) The sign of the weights of a logistic regression How do these images represent the weights? Would be ...
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How to frame this problem using RL?

How should this problem be framed in the domain of RL for preventing users from exceeding their bank account balance and being overdrawn? For example, a user has 1000 in an account, and proceeds to ...
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Hyper-plane in logistic regression vs linear regression for same number of features

Geometric interpretation of Logistic Regression and Linear regression is considered here. I was going through Logistic regression and Linear regression. In the optimization equation of both following ...
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