# Questions tagged [logistic-regression]

Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

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### Loss Function for Probability Regression

I am trying to predict a probability with a neural network, but having trouble figuring out which loss function is best. Cross entropy was my first thought, but other resources always talk about it in ...
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### For Logistic regression, why is that particular logistic function chosen as opposed to other logistic functions?

The logistic function used in logistic regression is: $\frac{e^{B_{0} + B_{1}x}}{1 + e^{B_{0} + B_{1}x}}$. Why is this particular one used?
345 views

### Two steps optimization of a credit card limit

I have a problem similar to what is on the title but not the same. The problem on the title allows me to explain the dynamics of my need. I have to determine what the optimal value is for a variable ...
70 views

### Issues with self-implemented logistic regression

I am trying to self-implement a logistic regression algorithm to do some self-learning but I am having a bit of trouble with achieving similar accuracy to the logistic regression of sklearn. Here is ...
250 views

### ML: Classification Model Comparison

Given is a dataset that I need to use for a classification and I want to compare the performance of different classification models. Let's assume, I want to look at logistic regression (with ...
356 views

### Error while plotting Logistic Regression Classification

I was trying to plot by using the following code ...
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### Why do we don't write units with MAE or RSME for regression problem ? If I wish to write the units when how do I identify the units for them?

I have referred many research paper but no one is talking about the units of the metrics. Do MAE , RMSE etc have some units ?
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### What is the best Classification Method alternative to Nominal Logistic Regression, if your Response and all Predictor variables are Categorical?

Hy, I need help in choosing the best classification method. My response variable is nominal with "4" categories and five predictor variables, two of them are nominal and three are binary. ...
660 views

### Binary classification with imbalanced dataset, about lightgbm output probability distribution

I trained a binary classifier for an imbalanced dataset. I did two experiments: lightgbm classifier, boosting_type='gbdt', objective='cross_entropy', SMOTE upsample After training the lgbm model, I ...
21 views

### Determine most important features in diagnostic data

I have a dataset of device diagnostics. I have two tables: one relating each device to failures code. Two devices can share a failure code for example a common chip malfunction. The second table links ...
21 views

### Best Method for Using Experts to Score Qualitative Data

TL;DR: Looking for recommendations or resources on the best method to have subject matter experts score qualitative data to train ML model. Problem: I am working on a problem in the biochemistry ...
665 views

### How to interpret my logistic regression result?

I'm having a hard time to interpret my result of the logistic regression. I have a few question. Firstly, how can I check if a feature is more important to the others, like that there is a real ...
453 views

### How to retrieve results summary from statsmodels GLM with regularization?

I'm trying to fit a GLM to predict continuous variables between 0 and 1 with statsmodels. Because I have more features than data, I need to regularize. ...
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### Connection between prob output LogisticReg/SVM and ROC

I have the following ROC generated using LPOCV and Logistic regression or SVM (l2 norm). Now, let's say I have a test set containing 10 patients and I get that the probabilities of those patients to ...
2k views

### Some of the p-values are NaN - logistic regression

I am trying to do logisitc regression, but have this issue - some of the p values are NaN ...
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### Probability of the recipient to open the email

I am trying to build a model using logistic regression, where my dependent variable is y=1 if the mail was opened, y=0 if it was not. I have data approximately 10 records (10 rows) for every ...
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### Interpretable models apart from Logistic Regression

I am wondering about other interpretable models apart from logistic regression. I am looking for models that can interpret the effect on the target variable by unit change in any feature variable. I ...
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### Logistic Regression Model for categorical features with multiple values in each category

I am working on an insurance use case to build a logistic regression classifier to predict if a policy will lapse or not. The dataset has more than 20 categorical features for a policy. Each ...
165 views

### Different results for LogisticRegression on python 2.7 and 3

I have different results for the same kernel on python 2.7 (local machine) and python3 (the system running on kaggle) for LogisticRegression. How it is possible? Here my results from my local machine:...
129 views

### Logistic Regression with Tensorflow

Is this the correct Estimator for Logistic Regression in TF 1.10? There used to be a function called: LogisticRegressor which is deprecated In README.md file it ...
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1 vote
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### Log odds vs Log probability

Log-odds has a linear relationship with the independent variables, which is why log-odds equals a linear equation. What about log of probability? How is it related to the independent variables? Is ...
1 vote
57 views

### Logistic Regression for prediction

I would like to ask about the theoretical approach of using Logistic Regression for customer data and more specifically Churn Prediction (in BigQuery and Python). I have my customer data for an online ...
1 vote
59 views

### Odds vs Likelihood

Odds is the chance of an event occurring against the event not occurring. Likelihood is the probability of a set of parameters being supported by the data in hand. In logistic regression, we use log ...
1 vote
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Log converts values from multiplicative scale to additive scale. What is the advantage of an additive model in logistic regression over a multiplicative model for which we use log?
1 vote
24 views

### Effect of log odds on skewed data

Does taking the log of odds bring linearity between the odds of the dependent variable & the independent variables by removing skewness in the data? Is this one reason why we use log of odds in ...
1 vote
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### Logistic Regression-Log odds calculation example

Can someone provide me an example/link of how log odds is calculated in logistic regression (with multiple independent variables)? All the examples I've come across explain log odds calculation with a ...
1 vote
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### Meaning of 'Closed Form'

Here's an excerpt from a paper explaining Logistic Regression. What does 'Closed Form' mean in this context? Please explain in simple terms. The definitions online are confusing. Gradient of Log ...
1 vote
176 views

### Difficulties in create a confusion matrix in R for Yes or No

I am new to regression and confusion matrix and trying to create a confusion matrix from logistic binary regression model. I am trying to create a confusion matrix from Yes or No values from the ...
1 vote
177 views

### MLE & Gradient Descent in Logistic Regression

In Logistic Regression, MLE is used to develop a mathematical function to estimate the model parameters, optimization techniques like Gradient Descent are used to solve this function. Can somebody ...
1 vote
405 views

### Relation between MLE (Maximum Likelihood Estimation) & Gradient Descent

What are the similarities & dissimilarities between MLE (used to find the best parameters in logistic regression) & Gradient Descent?
1 vote
24 views

### How to customize logistic regression for this case?

I have a binary classification problem, with a dataset comprising of several features. When I train LogisticRegression on it, I get large number of false positives ...
1 vote
16 views

1 vote