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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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 on my research: How can I do linear and logistic regression with the same neural network?
By example, what I mean ...
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Do I need to adjust frequencies or weights of rows so the right weight is given to each sample (data mining)?
The general problem type is as follows. I have about 2,500 rows of data. Each row contains data about an individual sample with sizes from around 10,000 to 200,000 (a known attribute / column), and ...
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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 ...
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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 ...
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I intend to do classification modelling, but my target variable has only one value
Currently I have a dataset and I am trying to predict whether someone will default on their bank loan.
The dataset is quite tricky. It covers those who have defaulted in the past, but is also ...
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1answer
62 views
improving accuracy of logistic model
I am trying to reproduce results from one paper, where authors minimized the following loss function
\begin{align}
\min_{w \in R^d} \frac{1}{n} \sum_{i \in [n]} log(1 + exp(-y_ix_i^Tw))+\frac{\lambda}{...
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1answer
40 views
Recursive Feature Elimination (RFE) with Logistic Regression and little correlation between the features and the target (SKLearn)
I have little experience in the field of Machine Learning, so I apologise in advance for my ignorance and lack of intuitions.
I'm trying to build a classifying algorithm to identify if a subject is ...
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1answer
21 views
Kohen Kappa Coefficient of Naive Bayes with 62% overall accuracy is better than Logistic Regression with 98% accuracy?
I have been trying to evaluate my models used on fire systems dataset with a huge imbalance in the dataset. Most models failed to predict any true positives correctly however naive Bayes managed to do ...
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23 views
Why ROC value area under curve of two models is different whereas accuracy, precision, recall, f1-score and confusion matrix is same
I am applying logistic regression and support vector machines on the extacly same dataset with 70% data for training and 30% for test. Both perform exactly the same have the same precision, recall, f1-...
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1answer
20 views
How to compute Hessian matrix for log-likelihood function for Logistic Regression
I am currently studying the Elements of Statistical Learning book. The following equation is in page 120.
It calculates the Hessian matrix for the log-likelihood function as follows
But is the ...
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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 ...
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What is the best way to find minima in Logistic regression?
In the Andrew NG's tutorial on Machine Learning, he takes the first derivative of the error function then takes small steps in direction of the derivative to find minima. (Gradient Descent basically)
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1answer
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Use all available data to build Logistic Regression model [duplicate]
Using K-Fold, I chose to use Logistic Regression for a project of mine.
I made it learn on my X_train (80% of data), and tested it on my X_test, with good results.
My question is : now that I need ...
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1answer
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LogisticRegression NotImplementedError on fit function
im a newbie in data science or machine learning. i try to implement code from here, but i got error when try to call fit function
here is the code:
...
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1answer
22 views
When can you reorder log operations?
For example, you can reorder a softmax + nl (negative likelihood)
to log_softmax + nll (negative log-likelihood)
Essentially changing log(softmax(x)) to softmax(log(x))
However, what are the ...
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2answers
44 views
Logistic Regression vs SVM
Following Andrew Ng's machine learning course, he explains how we can modify logistic regression to obtain SVM algorithm. First he replaces (sort of approximating) cross entropy loss with hinge loss ...
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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 ...
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How to validate logistic regression in SAS university edition
I am very new to SAS and I'm using the University Edition.
I was provided with a pre-made training and testing set.
I fit a binary logistic regression model with the training set, but now I want to ...
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l2-regularized regression in keras
I just started with Keras/Tensorflow and I am trying to reproduce results from one paper, where authors minimized the following loss function
\begin{align}
\min_{w \in R^d} \frac{1}{n} \sum_{i \in [n]}...
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1answer
29 views
I have 3 graphs of a binary Logistic Regression that I want to understand better what is happening and learn of a strategy to make the model better
My problem is the following: I have a binary Logistic Regression model with a very imbalanced dataset that outputs the percentage of the prediction. As can be seen in the images, as the threshold is ...
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1answer
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How does inverse of logistic function produces “linear relationship”, (so we can use least-squares)
I am reading about time-series analysis in "A First Course on
Time Series Analysis". The book reviews the logistic function ($f_{log}(t)$).
Part 1.6 (PDF page 16; book page 8; screenshot below) ...
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Reclassification machine learning measuring fatigue
I am very new to data science/ML field, so I apologize in advance if my logic may seem confusing.
I would like to know if it's possible to perform reclassification on a dataset?
So the process I ...
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1answer
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Error calculation in Logistic Regression
Suppose we have a linear regression model that predicts an item’s price. If the item’s prediction is 8 USD and the actual value is 10 USD, then it is clear that the error is pow(10-8, 2)=4.
But how is ...
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1answer
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Explanation for Why Logistic Regression can be so Accurate in Sentiment Classification?
My question is about how a logistic regression model performs so accurately. In some exploratory experimentation, I compared a logistic regression model against a long short term memory recurrent ...
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Is my model over fitting or not?
I have 50000 observations with 70% positive and 30% negative target variable. I'm getting accuracy of around 96-99% which seems unreal of course and I'm worried that my model is over-fitting which I ...
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1answer
25 views
Is this scheme correct for logistic regression with stochastic gradient descent
I am implementing logistic regression with stochastic gradient descent, but it is not working as expected. I've tried many epochs and different learning rates $\alpha$ but the probability of belonging ...
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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 ...
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2answers
85 views
Cannot make a single prediction: Is this behavior normal?
I am running a hate speech classifier published by Davidson et al.
The principle is simple, the classifier takes as an input an annotated ('hateful', 'offensive', 'neither') dataset of tweets. It ...
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How can I test my trained model on a completely new dataset? [duplicate]
Preface
I have an annotated text dataset on hate speech. Simply put, the dataset consists of a column called text which includes a piece of text, and a column ...
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1answer
69 views
Logistic Regression outperforms MLPClassifier
I am new in ML and I am trying to train classifier. I have a tiny dataset, just 90 examples, I divided it 70/30 train/test set and started to train.
As I know MLP must outperform Logistic Regression, ...
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2answers
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If a categorical feature only occurs a few times in a data set, should I drop it?
I have a data set of mostly categorical variables. When I one-hot encoded them some of the features occur less than 3% of the time.
For instance the Tech-support feature only occurs 928 times in a ...
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1answer
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How to select one record from multiple record for a subject during analysis?
I have a dataset where I am working on a binary classification. I have two classes of subjects. One is Outpatients and Other is Inpatients. (66:33 is the class proportion)
My objective is to identify ...
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1answer
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Require Guidance - Identifying risk factors
I have a dataset of patients who have been inpatients (admitted to hospital) and not admitted (but visited as outpatients). Class proportion is 66:34.
I have collected a list of features for all ...
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1answer
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Which metric to use for classify a binary logistic regression
I still novice in machine learning. My problem is as follow :
I use two binary logistic regression models for making comparaison. Additionally to LogLoss and accuracy, I would like to use for metric :...
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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?
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1answer
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Error while plotting Logistic Regression Classification
I was trying to plot by using the following code
...
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Logistic Regression Maximum Likelihood
Is it true that we assume our P(y|x;theta) to follow Bernoulli's distribution given y has binary output in Logistic Regression? Is there any specific reason why we consider Bernoulli's distribution?
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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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1answer
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Risk prediction vs classification model
I am working on a binary classification model. Currently, when I use scikit logistic regression, it outputs binary values like 0s and 1s. However, I understand, from online reading, that it outputs ...
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Class of prediction in logistic regression
Very elementary question:
While doing logistic regression(yes vs no), the coefficients shown by summary function.
My question is +ve coefficients supports to which class "yes" or "No"(or defaulter/...
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1answer
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Optimum values of all predictors in logistic regression
I am trying to figure out in logistic regression, with the help of coefficients of $x$ variables, we could figure out that on unit change in any $x$ variable what will be the change in probability of ...
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1answer
327 views
Why continuous features are more important than categorical features in decision tree models?
I have both categorical and continuous features in my prediction model and want to select (and rank) most important features.
I have converted all categorical variables into dummy variables using one ...
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1answer
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batched CrossEntropyLoss in pytorch
I'm wondering how to implement this with pytorch built-ins. I've got a 3 dimensional input of uints called policy. Most of the entries are zero, and if I were to L1 normalize this I would have a (...
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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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1answer
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Why results of statsmodel logreg is different from scikit-learn logreg?
I am trying to do a binary classification. I have only 6 input variables and one output variables. Label 1 is 1554 records and Label 0 is 3558 records.
As you can see below, the metrics that I get ...
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Advisory models apart from logistic regression
I am wondering, if we have some more advisory models apart from logistic regression?
That mean i am looking for models that can interpret the effect on y variable by unit change in any chance ...
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1answer
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How to use scikit metrics for a statsmodel or vice versa?
Am working on binary classification problem with 5K records. Label 1 is 1554 and Label 0 is 3558.
I did refer this post but not sure whether it is updated now or anyone has any way to compute this ...
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1answer
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Why and how to match variables in logistic regression?
I have a dataset of ~4.7K records focused on binary classification with 60 features. class 1 is of 1554 records and class 2 is of 3558 records.
Now I would like to find the risk factors that ...
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1answer
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About the maximum likelihood, when we convert the maximization problem into minimization, why we take the negative?
On page 12, we take $log$ on both side.
$\max_{\boldsymbol{w}}L\boldsymbol({w})=\max_{w}\displaystyle\prod_{n=1}^Np(t^{(i)}|x^{(i)};\boldsymbol{w})$
$\ell(\boldsymbol{w})=-logL(\boldsymbol{w})$
$\ ...
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1answer
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1: 10 rule in logistic regression - EPV
I have a dataset with 4712 records. Label Yes - 1558 records and Label No - 3554 records.
I read online that ...
