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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how to improve baseline logistic regression in high dimensional binary classification problem?

info about dataset: df.shape = (10000, 100) all feature are numerical values. few outliers in each column, column with most outlier have 0.7% of data as outlier. I am trying to improve on my ...
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Low scale ML/statistical techniques for data poor settings

I have two separate problems. One is logistic regression and other is time series prediction. But both suffer from paucity of data problems a) For logistic regression, I have tiny dataset with 10 ...
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Profiles classification

I've been working on a project where it consists of a dataset of profiles (50k rows) along with their position, age group and hobbies (200 columns). These features (except for the position) are graded ...
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Why is my training score below my testing score?

I'm learning data science, and currently practicing with the Titanic Dataset. I'm doing a simple logistic regression using scikit-learn, and plotting the learning curves of that model with Matplotlib: ...
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Preparing for interview - Logistic regression question

So I'm doing some exercises to prepare for a interview test. However there's one of the assignments I don't understand. Maybe some of you can explain what they want me to do? It would help me to ...
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How to select the significant cross-terms in logistic regression?

I have data where the number of feature vectors and the number of target classes are identical. I built a logistic regression model to learn the class of unseen data using training feature vectors ...
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Logistic regression with unbalanced data, scoring based only on rare class

I have a dataset off app. 600.000 data points in which 0.2% (1.200 samples) is labelled as signifying a rare event. I want to use logistic regression to help me predict this rare event, but even when ...
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How do we numerically update the decision boundary in case of logistic regression

In logistic regression classification, the initial decision boundary is defined as −2.7a − 2.2b + 15.2 = 0 How do we apply gradient descent to the initial decision boundary, to calculate the new ...
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I am confused about these models

In the first problem, it's been told to accept the maximum number of good customers, if at least 98% of the customers that are do not repay their debt correctly identified. I am confused about what is ...
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Which one first? Imputing missing values or dummy creation?

While working on model building using Logistic Regression, we did two different ways. Method 1: Created dummy variables before treating missing values. This resulted in 37 columns expanding to 192 ...
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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. ...
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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): ...
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What is the Intuition behind weight vector W which is normal to the plane? Is the weight vector W same as the W which is normal to the plane π?

In an interview, I was asked the intuition behind the weight vector. I told the weight vector is a vector which we try to minimize to a local minima with the help of regulariser so we don't overfit. ...
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Predicting % of demand going to each product

I work within an industry with products that expire, therefore we would like to be able to choose which specific marketing keywords we should switch on to drive demand to the products that are over-...
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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. ...
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Baby cry detection model using binary classification through logistic regression

I need some help regarding my final year project. I am fairly new to machine learning and I have tried a lot to understand how to train a model using logistic regression. I have two datasets of audio ...
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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 ...
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How to interpret feature weight coefficients in logistic regression for text classification?

I am working on a simple text classification problem where I have as inputs tweets and as class whether that tweet contains fake news or not (0 is real news, 1 is fake news). I have trained a logistic ...
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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 ...
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How can i solve the classification's problem with cross validation in LogisticRegression?

I want to make a data frame with most repeated word in sentences and make a classification via Logistic-Regression. I tried to write the steps clearly in codes. ...
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Math of Logistic regression cost function

In the current scikit-learn documentation for binary Logistic regression there is the minimization of the following cost function: $$\min_{w, c} \frac{1}{2}w^T w + C \sum_{i=1}^n \log(\exp(- y_i (X_i^...
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38 views

How to predict when and why of hospitalization?

I have an EHR data source which has info on a) Patient visit records (Inpatient, outpatient, Emergency etc) and why did he visit hospital (diagnosis codes attached to each visit) b) Patients drugs ...
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Which features are causing a class to be classified correctly or incorrectly?

I am doing a project that involves training and testing different algorithms to predict a developer's profile type (Frontend, Fullstack, QA, ML, etc.) using that developer's skills (AWS, Selenium, ...
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Residual Deviance in GLM Output in Python vs. R

I am coming from R to Python for econometrics. In R, in case of fitting a logistic regression with glm, the output summary would include the result of test of the proposed model against the saturated ...
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Effect of a few wrongly scaled feature values on logistic regression model

I was given a situation to predict the validity of the logistic regression model when it was found that certain values of a heavily weighted feature were found to be erroneously multiplied by 1000. ...
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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 ...
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Having trouble scaling scores of logistic regression

I am constructing a credit scorecard using logistic regression, similar to the one shown here. However, when trying to convert the coefficients of logistic regression into score representation (by ...
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How to interpret my logistic regression result with statsmodels

so I'am doing a logistic regression with statsmodels and sklearn. My result confuses me a bit. I used a ...
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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 ...
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Selecting a boundary on a binary classifier to optimal precision and recall

I have a logistic regression classifier that shows differing levels of performance for precision and recall at different probability boundaries as follows: The default threshold for the classifier to ...
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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 ...
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Concatenating embedding and hand-designed features for logistic regression

An interviewer told me that we cannot concatenate an embedding from a neural network (such as a pre-trained image representation) and hand designed features (such as image metadata) for use in a ...
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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 ...
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Bad results in Logistic Regression from-scratch Python implementation on sample gender data

I am quite a newbie to Machine Learning, now trying to implement from scratch in Python (using numpy) a logistic regression algorithm. I took the gender/height/weight data from here. Then I did the ...
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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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Finding value of theta in linear classification

I have an examing coming up, and I'm practicing with exams from previous years. However, the answers to the questions are not provided unfortunately. I'm currently doing the question below, and the ...
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Prediction problem across a wide space of Clash Royale card games

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 ...
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SKLearn - Understanding Discrepancy Between LogisticRegressionCV classification_report and scores_

Cross-posting from Stack Overflow: I'm running into a weird situation where my sklearn LogisticRegressionCV model is apparently getting 100% accuracy (the lack of ...
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How to improve results from ML model? (spam classification)

I am trying to build a model that predicts if an email is spam/not-spam. After building a logistic regression model, I have got the following results: ...
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How Do I Plot a Nonlinear Decision Boundary? [duplicate]

I finished training my Sci-Kit Learn Logistic Regression model and it is performing at 100% accuracy. However, when I went to plot the decision boundary, I got a bit confused. I am not running the ...
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How to determine a sufficient number of training examples for a linear regression classifier?

How do we determine a sufficient number of training examples for a linear regression classifier? What kind of behaviors might we expect if we use too few training examples?
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In multinomial logistic regression, how to explain the softmax outputs properly?

I tried to solve multiclass problem ("cat", "dog", "horse") problem and figured out that the more words in test text, the more difference between classes. I grouped the ...
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Logistic Regression performs better on longer texts

I trained the LogisticRegression model with TF-IDF (both birgams and unigrams) and while predicting class it revealed that in longer texts (up to 3000 symbols)it works better that if I use short (+-...
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Neural Network probabilities problem

I am using machine learnig to measure probability for the outcome of tennis matches. If the winer is 1 that means that p1 won otherwise p2 won. in Columns LG, SVC, RF and NN there are probaiblities ...
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Non-linear decision boundary in logistic regression algorithm with polynomial features

Lately I have been playing with drawing non-linear decision boundaries using the Logistic Regression Classifier. I used this notebook to learn how to create a proper plot. Author presents a really ...
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115 views

Logistic Regression Manual Update

For the logistic regression below, how can I manually update the coefficients a and b manually? EDIT y = 1.0 / (1.0 + exp(-ax - b)) after observing the following ...
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From logistic regression to XGBoost - selecting features to run the model with

I have been asked to look at XGBoost (as implemented in R, and with a maximum of around 50 features) as an alternative to an already existing but not developed by me logistic regression model created ...
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51 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 ...
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Assessing model performance on different sub-segments [closed]

I am currently working on a credit risk related project where i built a binary logistic regression model for an imbalanced dataset. According to the regulations i have to prove that the model performs ...

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