# 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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### 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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### Goodness on test or train set?

I split my data set before on train (80%) and test (20%) splits. Trained logistic regression model on the train set. Now, want to check the goodness of fit using the Chi-square likelihood omnibus test,...
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### Is a simple linear regression appropriate for an originally ordinal outcome variable?

Context: To form an index, I summed (and weighted) 2 variables containing ratings (1-9). Potentially problem: Wondering if it is appropriate to conduct a linear regression, all other assumptions being ...
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### Predict data using Pre-Trained Classification Model

I have pre trained classification model (saved as pickle file) to predict employee attrition. My question is when I use new dataset to predict using Pickle file do I need do all preprocessing steps (...
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### Using class weights with training on imbalanced dataset gives worse result w.r.t logloss than without weights

I am trying to make a model for usual binary classification that is able to predict probabilities of classes. I have not very big dataset of 10k objects where classes are imbalanced as 80:20 and tried ...
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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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### LSTM basic doubt

How LSTM are able to figure out that a particular word has occurred. Like in classical algos, We have column order. But in LSTM, Since each cell receives different words, How does it know a particular ...
1 vote
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### NLP logistic regression

A basic doubt I have, Usually when dealing with text data for classic ML algos, We use Tf-idf which uses entire vocabulary for each row and assigns some weighted value. My doubt is can I use 5 feature ...
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### How do I modify a Logistic Regression to target a specific point on the ROC curve?

From a conceptual standpoint I understand the trade off involved with the ROC curve. You can increase the accuracy of true positive predictions but you will be taking on more false positives and vise ...
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### How to generate a rule-based system based on binary data?

I have a dataset where each row is a sample and each column is a binary variable. The meaning of $X_{i, j} = 1$ is that we've seen feature $j$ for sample $i$. $X_{i, j} = 0$ means that we haven't seen ...
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### What to do when one feature has very large importance/weight?

I am new to Data Science and currently am trying to predict customers churn for a company that offers of subscription-based bookings management software. Its customers are gyms. I have a small ...
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### The accuracy depends on the hyper-parameter in a strongly non-monotinic way

I have a data set labelled with a binary classes. I calculated the principal components from the data, then made the PC transformation. The goal is to find an optimal number of PCs so that the binary ...
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### Determining increments for aggregated time series data to determine impact of individual features

I'm working with a data source that provides itemised transactions, which I am aggregating into 1 hour blocks to determine a 'rate per hour' as the dependent or target variable - i.e. like a time ...
1 vote
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### Industry analysis - multiple industries

I am trying to run logistic regression on marketing leads and use industry as a predictor of whether the lead converts (1/0). Often, when I enrich data from websites like crunchbase the associated ...
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 ...
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### Is there a random forest env (sci-kit, TFDF, R, etc) that has an implementation for multi-output regression?

It is easy to adapt the idea of tree based linear regression to perform logistic regression: The decision boundaries of the tree divide the space of independent variables into hyper-cubes, and each ...
1 vote
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### What to do about a predictor with a feature importance so high above the others that it is the only determining factor in my machine learning model?

I created a logistic regression model with scikit-learn which predicts the outcome of an NFL football game. It predicts the result based on features such as the team's record, opponent's record, pass ...
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### NAN in keras neural network results

I am creating a neural network simple architecture. But I keep getting NAN in result, cant figure out why, below is my code. ...
1 vote
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### 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 ...
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### Why coefficients from logistic regression are not proportional to bad rate?

I am building a logistic regression model in Python with statsmodels.api.Logit. The model contains 12 features that are encoded using ...
1 vote
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### Trying to perform elastic-net regression in R

I am new to R and Elastic-Net Regression Model. I am running Elastic-Net Regression Model on the default dataset, titanic. I am trying to obtain the Alpha and Lambda values after running the train ...
1 vote