# Questions tagged [logistic-regression]

For questions about logistic regressions, a regression model where the dependent variable is categorical.

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### Properties of the bifurcation diagram for the logistic function

Once the bifurcation diagram has been plotted ($x_{n+1}=rx_n(1-x_n)$), there are 3 elements or properties that I don't know haw to explain, and I have not found any article where they are explored. ...
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### Logistic regression, when is a "True Positive"?

I have the following table, (LR = Logistic Regression; BA = Biological activity): ...
1 vote
38 views

### Maximal accuracy of logistic regression on the n-parity problem

Consider the standard logistic regression ('LR') function, $y = \sigma(w^T \cdot x + b)$, where $\sigma$ is the logistic function ('sigmoid'). When checking the accuracy, we will consider the argmax ...
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### Multinomial Logistic Regression likelihood

Suppose we have the following parametric model for logistic regression: $$\phi_{i} = \frac{\exp{(a^{T}x_{[i]}})}{\sum_{k = 1} ^{M} \exp{(a^{T}x_{[k]})}}$$for $i = 1, \dots, M$ and that the parameter ...
• 167
1 vote
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### Show that the random vector follows a multinomial distribution and find it's parameters.

I am trying to show the following in the below setup, I have written my answers and approach below. I am having a hard time understanding the second and last part, especially the last part. Consider ...
• 1,106
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### Interpret the logistic regression coefficient.

I am running a logistic regression model in r to study the link between customer procrastination and whether customers repurchased. The dependent variable is whether customers will repurchase the item....
1 vote
107 views

### logit and probit models

Basic background Hi, I'm relatively new to statistics and mathematics stack exchange so please bear with me. I'm trying to learn about the probit and logit models where the observables $y$ can only ...
• 11
1 vote
361 views

### Derive the derivative of cost function of logistic regression.

I am trying to derive the derivative of the loss function of a logistic regression model. Instead of 0 and 1, y can only hold the value of 1 or -1, so the loss function is a little bit different. ...
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