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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392 views

Logistics regression with polynomial features vs neural networks for classification

I am taking Andrew Ng's Coursera class on machine learning. He mentions that training a logistic regression model with polynomial features would be very expensive for certain tasks compared to ...
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28 views

How do we decide on the classification algorithm to use with huge training size?

I am solving a questions binary classification problem and the training size for this is huge(291 billion). The data has bloated because of using tfidfvectorizerfor ...
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239 views

How to do predict a new sms to be spam or not?

I have trained a model for spam classification - This is my code - ...
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281 views

Why do we divide the regularization term by the number of examples in regularized logistic regression?

So this is the formula for the regularized logistic regression cost function: $x^{(i)}$ - the $i$'th training example $\theta_j$ - the parameter of the $j$'th feature $m$ - the number of training ...
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Do pseudo r squared metrics make sense for classifiers that aren't logistic regression?

I'm working with some domain scientists that are used to using logistic regression to predict a binary value. One of the ways they evaluate their logistic regression model is through the Nagelkerke $...
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86 views

Testable hypotheses construction; minimum predictive strength vs. significance

Is this null hypothesis TESTABLE? Research Question: "Can a predictive model utilizing logistic regression be built which predicts at least one customer will churn in 90 days, and this individual ...
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1answer
38 views

Can a Logsitic Regression model continue making predictions after removing predictions from the data set?

I have a logistic regression model that predicts churn (0 vs. 1). I was asked to use the model to predict on a historical group of non-churners, remove anyone who was marked as a churner, and then ...
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1answer
35 views

How to find what events cluster together?

I have a data set that looks at a five-year timespan of peoples' lives and indicates if specific events have occurred (Divorce, Birth of Child, Health Shock, etc.). ...
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30 views

Significance of AUC score

My model (Logistic Regression) has AUC score of 0.8 Am I right in stating that the probability of the model ranking a random positive sample higher than a random negative sample is 0.8? Also, how ...
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1answer
74 views

Depending samples in ad ranking and click rate prediction

I am struggling with the following problem: Suppose we fit a machine learning model to model advertisers click rates. I used a Logistic Regression approach using a one-hot/dummy encoding. We have ...
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2answers
100 views

Regression Algorithms in Production

I am interested in predicting if a doctor would prescribe a specific drug and have chosen Logistic Regression as a starting point. I have a few questions: Is feature selection the first step to take ...
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136 views

How to use logistic regression with decay

I have a dataset with binary outcomes. I use Logistic regression for making the prediction. example of my data : ...
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100 views

Is there any way to use (update) a pre-trained logistic regression model for data with new set of columns?

I am building an insurance recommendation engine. I have used some variables, like demographics, and built the model. Now I have claims data. Is there a way to include the new data without restarting ...
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1k views

How to calculate pedigree function in diabetes prediction?

I am developing a model for diabetes prediction using this dataset using Logistic Regression. I have completed the model and my input variables are - Pregnancies, Glucose, blood pressure, BMI, ...
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101 views

Measuring the similarity between a numeric data matrix and one or more categorical variables?

Given a numeric data matrix $A$ of size $n \times p$, which each row represents an observation along $p$ variables, and a second categorical data matrix $M$ of size $n \times z$, where each row ...
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182 views

AUC ROC Threshold Setting in heavy imbalance

I am doing binary logistic regression on a dataset with very heavy class imbalance. Class 1 is only 1% of data. When I train logistic regressor without class weights I get ROC AUC Score of 0.6269. ...
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49 views

Huge cost not converging well with TensorFlow logistic regression

I try to use Logistic Regression for a dataset which contains 15 numeric features and 4238 rows of examples. The calculated cost started at 415.91, and converged when the cost was reduced to 220.119 ...
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50 views

Logistic Regression performing better than SVM with a Gaussian kernel performing better than a linear SVM

I am very new to machine learning. I am working with a data set, and my algorithm for logistic regression (with lasso regularization) is performing fairly well (~0.8 AUC), my SVM with a Gaussian ...
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5k views

When to use Random Forest

I understand Random Forest models can be used both for classification and regression situations. Is there a more specific criteria to determine where a random forest model would perform better than ...
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1answer
120 views

Automating Logistic Regression

I have $3$ datasets I'd like to run a logistic regression on split into $X_1, y_1$ $X_2, y_2$ $X_3, y_3$ How can I run a loop so that I can run an automated ...
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53 views

Manually changing coefficients of a model

Is there a way to manually change parameters of a model in Orange 3? I have a dataset and trained a logistic regression model on it. Now, I can alter the coefficients (beta values) of the logistic ...
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3answers
364 views

Logistic Regression doesn't predict for the entire test set

I am working through Kaggle's Titanic competition. I am mostly done with my model but the problem is that the logistic regression model does not predict for all of 418 rows in the test set but ...
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In the context of image binary classification, is it necessary to divide dataset into true positive, false positive, true negative, false negative?

I am working through this course. It seems that the professor is not dividing the dataset into true positive, false positive, true negative, and false negative. In the context of image binary ...
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646 views

What is the purpose of Logit function? At what stage of model building process this logit function is used?

We have two prominent functions (or we can say equations) in logistic regression algorithm: 1. Logistic regression function. 2. Logit function. I would like to know: a. Which of these equation(s) is/...
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812 views

Why does the logistic regression cost function need to be the negative of log?

I am going through this course. The professor is talking about the logistic regression cost function: $$ P(y|x) = \hat y^y (1- \hat y)^{(1-y)} $$ Taking log on both sides provides: $$ \begin{align} ...
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39 views

Data Structure For Multilevel Analysis

I am little confused about how to structure my specific data for multilevel analysis. I have 10 categories and each category has some items in them. The dataset is available for 117 weeks. There is ...
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184 views

If categorical variable has some hierarchy, should I just label them or split into dummy variables (One-Hot encode)?

I have a column which has 5 unique categories. There's a hierarchy between these categories (Best > good > OK/Not Sure > Bad > Worst) In this case, should I label them based on hierarchy like: ...
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55 views

Is there a representation of the separating hyperplane in t-sne?

I have used t-sne to visualize a set of images which I have used for training a binary classifier. Let us assume that the binary classifier is trained to detect cat(1) vs. no-cat(0). I have used the ...
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1answer
2k views

Automatically Remove highly correlated features using Variance Inflation Factor?

I want to be able to automatically remove highly correlated features. I am performing a classification problem using a set of 20-30 features and some may be correlated. Multiple features can be ...
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23 views

Penalization term for unfairness

I am reading [1], where the researchers do a logistic regression, but add to the loss function the following penalization term for fairness $ R^{AVD}_{FP}(\theta; S) = \left\lvert \dfrac{\sum\limits_{...
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127 views

Interpretation of ROC AUC score

i tried to evaluate 6 models and after plotting , this what i get : So i'm wondering , if those results are "Right" ? Thank's in advance.
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180 views

Logistic Regression - ROC curve plots Sensitivity vs Specificity instead of (1-Specificity)

I am new to Machine Learning and have been doing some practice on Logistic Regression. To evaluate the models, I've been trying to create some ROC plots. The package that i used is pROC. The model ...
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1answer
70 views

Can one use non converged results from Logistic Regression?

I'm running Logistic Regression on a dataset for a classification problem. I used the model on the dataset when it was normalized and I had no problem with it converging. Now, I wanted to see the ...
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1answer
1k views

Logistic Regression - Coefficients have p-value more than alpha(0.05)

I am very new to the machine learning field and have been practicing logistic regression on few sample data sets. I have built a Model using the logistic regression algorithm. Few of the coefficients ...
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Why does a machine learning model of English can not be directly applied on right to left languages, like Arabic Hindi, and Urdu

I have a Logistic Regression model that works fine when used with an English Dataset. But, when I pass a same format data set in a different language, (Language is URDU which is right to left and UTF-...
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1answer
67 views

Using a feature in prediction even if it gets zero as p-value?

I created two binary classification based logistic regression models and I got these results: Model 1: Accuracy: 67.51% AUC: 65.21% Model 2: Accuracy: 67,99% AUC: 65,70% The second ...
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79 views

Accuracy of the model

I'm using this dataset and i'm trying to do logistic regression ...
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16k views

How to plot logistic regression decision boundary?

I am running logistic regression on a small dataset which looks like this: After implementing gradient descent and the cost function, I am getting a 100% accuracy in the prediction stage, However I ...
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267 views

Use text classifier on unseen data

I've trained a few models to classify between two categories of text. Logistic regression was the best. Now how can i test it on unseen data? I tried this: ...
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291 views

which metric is better for boosting methods

I work on a dataset of 300 000 samples and I try to make a comparison between logistic regression (with gradients descent) and a LightBoost for binary classification in order to choose the better one. ...
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1answer
116 views

How to interpreting the exponential coefficent in poisson regression with offset?

I am trying to find the village level risk factors for malaria. Therefore, I ran a poisson model in r with the prevalence of malaria(y) as dependent variable, altitude(x1) and Forestation(x2) as ...
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1answer
71 views

What happens to a machine learning technique (specifically Decision Tress and Logistic Regression) if the validation dataset has a new category?

Let's suppose I have a dataset which has a categorical variable and the problem I am solving is a classification one. This categorical variable var has ['A','B','C'] as the possible set of data. ...
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1answer
18 views

Machine Learning Dataset: Easy enough for fully connected, but not easy enough for logistic regression

I was wondering if someone could direct me to a dataset for a classification task with the following conditions: Multinomial logistic regression alone does not learn a good classifier A series of ...
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1answer
474 views

Distribution of error values in linear regression vs logistic regression

Why do error values in linear regression have to be normally distributed and why not in logistic regression?
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564 views

Why did Logistic regression perform better than svm? [closed]

I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G]. I have tried different ML algorithms and found that Logistic regression out ...
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644 views

Making Prediction on logistic regression using SAS

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157 views

logistic regression : highly sensitive model

I am a newbie to data science and ML. I am working on a classification problem where the task is to predict loan status (granted/not granted). I am running a logistic regression model on the data. ...
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1answer
1k views

Normal distribution instead of Logistic distribution for classification

Logistic regression, based on the logistic function $\sigma(x) = \frac{1}{1 + \exp(-x)}$, can be seen as a hypothesis testing problem. Where the reference distribution is the standard Logistic ...
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169 views

Data prepration for logistic regression : Value either “not available” or a “year”

I have some data of houses that have been renovated. In my data there is one column (among others) that captures this information. It is either "-1" if there has not been yet any renovation, or the ...

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