Questions tagged [logistic-regression]

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

124 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
7
votes
2answers
1k views

Loss Function for Probability Regression

I'm 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 ...
3
votes
1answer
155 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 how much is the optimal value for a ...
3
votes
4answers
112 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 ...
3
votes
1answer
173 views

Error while plotting Logistic Regression Classification

I was trying to plot by using the following code ...
3
votes
1answer
1k views

How many coefficients does the Logistic regression model has as a function of the number of features?

I have built a logistic regression model using Python anaconda and was surprised to see that the number of model coefficients turned out to be proportional to the training sample size i.e. My ...
2
votes
1answer
39 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 ...
2
votes
1answer
78 views

Regularization for intercept parameter

Why is the regularization parameter not applied to the intercept parameter? From what I have read about the cost functions for Linear and Logistic regression, the regularization parameter (λ) is ...
2
votes
0answers
15 views

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 ...
2
votes
0answers
870 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 ...
2
votes
0answers
71 views

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 ...
2
votes
0answers
25 views

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 ...
2
votes
1answer
100 views

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 ...
2
votes
2answers
111 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:...
2
votes
0answers
125 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 ...
2
votes
0answers
23 views

When should the bias b be updated with weights w and when should it be updated seperately?

It seems in some Machine Learning models, the bias term $b$ is updated just like other weights $w_i, i=1...n$. For example, in Logistic Regression, using SGD, $b \ \text{or} \ w_0$ is updated with: $$...
2
votes
0answers
58 views

What Is The Difference Between Additive Natural Cubic Splines and Tensor Product Natural Cubic Splines?

Good day. Taking into account the picture shown, using tensor product is computationally expensive considering the fact that it has higher dimensions. I am just thinking why it is compared both ...
2
votes
0answers
64 views

Is it possible to run logistic regression on data with a few longitudinal parameters?

Currently, I am building a credit rating model based on logistic regression and faced a problem with inserting panel variables in it. Is it possible to do so in logistic regression and if it is, what ...
2
votes
0answers
97 views

What are some machine learning problems that can be attacked with continuous multiobjective optimization?

I am working on continuous vector optimization, and hence continuous multiobjective optimization is a particular case. I am interested in finding applications in machine learning for this problems. Is ...
2
votes
0answers
337 views

Learning ranking

This is a sort of a follow-up to this newbie question:Suppose I want learn ranking (so, I have a bunch of data points, ranked $1, 2, 3, ...$ Now, one way is to use something like logistic regression ...
2
votes
0answers
103 views

Type of Test to Determine Correlation in R

I have a dataset of approximately 48,000 rows each one a click of a an article, some of these clicks were also comments. For each article I have the country and subject of the article and name of ...
2
votes
0answers
558 views

Sales Dataset to determine best model for predicting future sales

We have a set of products in which we are trying to determine which products we should continue to sell, and which products to remove from our inventory. The file contains BOTH historical sales data ...
2
votes
0answers
37 views

Outputting risk groups for a logistic regression model

I have a problem with outputting the terms for a logistic regression model in R. For a given list of independent values, say list l of terms {w,y,z} to determine dependent variable {x}, I want to ...
2
votes
0answers
123 views

Random Forest Class Weighting for Logistic Probabilities

I have a model at work that I am building and am running into some odd outputs from the random forest as it pertains to the probability of response. In my case, the class distributions are very ...
2
votes
0answers
515 views

SAS Nested Likelihood Ratio Test for a Logistic Model

Using SAS Studio (online, student version)... Need to do a "nested likelihood ratio test" for a logistic regression. Entirety of instructions are: "Perform a nested likelihood ratio test comparing ...
2
votes
0answers
471 views

How to Interpret Multinomial Specification in R's `mnlogit` package

The mnlogit package in R allows for the fast estimation of multinomial logit models. The specification of forumlas is a bit different from most other regression ...
2
votes
0answers
86 views

Cross-sell models and additional holders

I would like to pose a question about how to treat additional holders in the propensity-to-buy models of banking products. Up to now I was only taking into considerations the clients as first holders....
1
vote
0answers
18 views

how to add cross term in logistic regression model?

I have a data of 2000 (say locations of different fruits grow) and 10000 (say factors responsile for growth of fruits). And I also know that there are 20 different types of fruits in these locations. ...
1
vote
0answers
35 views

Normalizing and joining of independent logistic regression model's prediction

I need to train several Logistic regression models on a different set of data (with a different set of labels): ...
1
vote
0answers
18 views

Simple constraints on Logistic Regression

I am doing with a binary classification problem. I have three features (w1x1 + w2x3 + w3x3 + w4), and I want to get a rule so that there is for sure w1 > 0, w2 > 0, w3 < 0 and any constant. ...
1
vote
1answer
30 views

Derivative of a custom loss function with the logistic function

I have costum loss function with $\mu ,p, o, u, v$ as variables and $\sigma$ is the logistic function. I need to derive this loss function. Due to multiple variables in the loss function, I need to ...
1
vote
1answer
43 views

How to combine two logistic regression models trained on different set of data?

My data has a hierarchy structure - meaning that there is an N class at level 1 and an M class at level M. After training both models separately with a different set of data (both are Logistic ...
1
vote
0answers
67 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 ...
1
vote
0answers
49 views

Best practice to select precision vs. recall threshold for a binary classifier

I have a logistic regression model in Scikit-Learn doing a binary classification. Looking at the Roc curve for the classifier I can see that it performs really well: The AUC score is 0.99 which is ...
1
vote
0answers
17 views

analyze the effect of some new changes to business rules on customers retention and sales

I am trying to analyze the effect of a particular business rule on customer behavior. Background: I have two call centers operating in my company. One is an in-house call center and the other one is a ...
1
vote
0answers
9 views

Prediction problem across a wide space

I have assembled a database of Clash Royale games in an attempt to understand the outcomes of various match-ups. The game is composed of an 8 card deck drawn from 102 cards. As you can see from the ...
1
vote
1answer
49 views

Predictive model to maximize sum of dependent variable?

I am trying to classify cars for a towing company. Junky cars earn more when sent to the junkyard, and the more valuable cars should earn more at the auction, despite the auction fee. Creating a ...
1
vote
0answers
16 views

How many positive responses are good enough for building a marketing response model when the response rate is low(0.5%)

We are planning a marketing campaign to collect data and the response rates for a random sample. Total population size is 10 million and historically, response rates are low (0.5 - 0.65 %). How long ...
1
vote
0answers
88 views

What's the order in applying SMOTE transformation in a pipeline?

Here's the thing, I have an imbalanced data and I was thinking about using SMOTE transformation. However, when doing that using a sklearn pipeline, I get an error because of missing values. This is my ...
1
vote
2answers
33 views

Classification report question

I need some help to interpret the 2 classification reports of the same logistic regression. The only difference between them is the size of test_size. Even though my second classification report has a ...
1
vote
0answers
15 views

Gradient calculation for proportional odds (logistic) model

I am trying to calculate a gradient for a proportional odds model. http://fa.bianp.net/blog/2013/logistic-ordinal-regression/ What steps are required to take the derivative with respect to w? $$\...
1
vote
0answers
41 views

Linear and logistic regression output with same neural network

it seems like this should be a very common task, but I have not found anything useful in my research: How can I do linear and logistic regression with the same neural network? By example, what I mean ...
1
vote
0answers
25 views

What to do when feature engineering and parameter tuning don't add to the base model performance

I've been working on using LogisticRegression from scikit to try the Titanic Kaggle comp. I've found something interesting, and that is that no amount of feature engineering and paramater tuning is ...
1
vote
1answer
30 views

Two questions on hyper-parameter tuning

Question 1: In the example of logistic regression, I often see the regularization constant and penalty methods being tuned by a grid search. However, it seems like there are a lot more options for ...
1
vote
0answers
20 views

scaling credit risk scorecard

I need to build a credit risk scorecard using logistic and linear regression. The variables using to predict are all dummies, where each dummy is a bin of some variable. Let's say the variable age, I ...
1
vote
0answers
17 views

KS-Score Methods

I came across 2 methods to calculate KS-Score and select best probability threshold. Decible Method TPR - FPR Is there any specific scenario on which it depends which method to select. or we cna ...
1
vote
0answers
12 views

What could be the impacts on the intercept and slops of each predictor in Logistic Regression by rare event cases?

I am wondering how data set with rare event cases would impact on my Logistic Regression model in terms of the intercept and slopes of each predictor?
1
vote
0answers
267 views

Feature importance using logistic regression in pyspark

I am using logistic regression in PySpark. I have after splitting train and test dataset ...
1
vote
0answers
79 views

Logistic regression, where is my mistake

I am doing assigment on Logistic Regression on Andrew Ng DL course, and can't understand where is my mistake, ...
1
vote
0answers
314 views

Python, Logistic regression - How to calculate Nagelkerke pseudo r squared

I am doing logistic regression in sklearn and I would like to calculate (Nagelkerke) pseudo r squared, which makes more sense for logistic regression analysis. I don't see it is available in sklearn ...
1
vote
0answers
48 views

Low ROC AUC with good Information Value

I'm trying to build my first application scorecard with Logistic Regression and getting low ROC AUC score (about 0.7). Dataset ...