Questions tagged [logistic-regression]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
409
questions
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1answer
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2
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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
...
2
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0answers
19 views
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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3
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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
...
3
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1answer
34 views
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 ...
1
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0answers
28 views
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/...
1
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1answer
18 views
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 ...
6
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1answer
136 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 ...
2
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1answer
34 views
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 (...
2
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0answers
41 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 ...
1
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1answer
28 views
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 ...
0
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0answers
6 views
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 ...
1
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1answer
27 views
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 ...
2
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1answer
26 views
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 ...
4
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1answer
40 views
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.
$\max_{\boldsymbol{w}}L\boldsymbol({w})=\max_{w}\displaystyle\prod_{n=1}^Np(t^{(i)}|x^{(i)};\boldsymbol{w})$
$\ell(\boldsymbol{w})=-logL(\boldsymbol{w})$
$\ ...
0
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1answer
39 views
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 ...
0
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0answers
54 views
Why a significant risk factor doesn't increase AUC-score/F1-metric?
I have a binary classification problem with 5K records and 60+ features/columns/variables. dataset is slighlt imbalanced with 33:67 class proportion
What I did was
1st) Run a logistic regression (...
1
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1answer
29 views
How to interpret statsmodel output - logit?
I ran a logit model using statsmodel api available in Python. I have few questions on how to make sense of these
1) What's the difference between ...
1
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1answer
50 views
difference between feature interactions and confounding variables
Let me define the problem space.
I am working a binary classification problem. I am trying to build a causal model as well as predictive model.
My aim is to find list of significant features (based ...
2
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1answer
32 views
Can we apply to GridSearchCV to Logistic regression .?
When I apply GridSearchCV to my model Logistic Regression, it's continuously throwing below error.
I understand that it's trying to convert string to float. But that's was my data. So how can I ...
3
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2answers
81 views
How to adjust cofounders in Logistic regression?
I have a binary classification problem where I apply logistic regression.
I have a set of features that are found significant.
But I understand that Logistic regression doesn't consider feature ...
1
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0answers
21 views
Feature importance using logistic regression in pyspark
I am using logistic regression in PySpark. I have after splitting train and test dataset
...
2
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1answer
30 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
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1answer
316 views
How to interpret coefficients from logistic regression?
I ran a logistic regression (statsmodel) on my data with 60 features using the below code
...
0
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2answers
41 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:...
0
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0answers
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Handling data with exactly same features but slightly different outputs? [Regression Problem]
I have a dataset where if I remove two attributes, in some cases remaining features are exactly the same but target value changes slightly. In my test set, I don't have those removed attributes so I ...
0
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0answers
163 views
Python - Logistic (Logit) Regression - why am I getting an Endog error?
I'm running the following code:
...
1
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1answer
14 views
Error while using predict [closed]
After splitting into test and train the glm function is used on train set. For example
m1 = glm(target ~ ., data = train, family="binomial")
Then
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0
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2answers
36 views
Logistic regression threshold value
How can i set the threshold value for the target variable. For example if a target variable is chance_of_admit and it has values from 0 to 1, how can I pick a value and so that I can convert it to 0's ...
0
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0answers
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Code for churn column
Problem Statement --
A Newspaper Publishing Company (NPC) is facing increasing churn rates since years.
This evolution has been jumpstarted by the rise of news- websites, and has
continued at an ...
2
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1answer
33 views
Predict_proba() probabilities distribution [closed]
I’m trying to calculate probability of class 1. I’m using gradients boosting (catboost classifier)
Is it normal to have an equal rate of positive classes in every predict_proba() bucket? e.g.:
[...
0
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0answers
20 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,
...
0
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0answers
59 views
Logistic Regression Plotting Learning Curve and Decision Boundary with Python
I already trained a dataset with Logistic Regression. However , I could not find any plotting code blocks of learning curve and decision boundary of my trained data. I put my codes at below. So , how ...
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2answers
25 views
Universal function approximation with fixed values (as vector or matrix)
I was thinking about way to represent/approximate universal function and came up with the idea that a plain fixed numbers could be used to represent pretty much any function on a fixed interval.
I ...
0
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2answers
124 views
Managing NaN in target variables (testing)
Please can someone advise me on how to handle NaN in my target variables set?
I've tried a variety of things but none is working. Here's what I've tried:
Imputing zeros (0) in Y_test
Replacing NaN ...
0
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1answer
128 views
Variation in output of Logistic Regression when using SMOTE
I am working on a logistic regression case with an imbalance in the target variable. To fix this I am using SMOTE (Synthetic Minority Oversampling Technique), but each time I run my regression model, ...
0
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0answers
169 views
Derivative of logarithm of loss function. Logistic regression
I am reading machine learning literature. I found the log-loss function of logistic regression algorithm:
$$
l(w) = \sum_{n=0}^{N-1}\ln(1+e^{-y_nw^Tx_n})
$$
Where $ y \in {-1;1}, w \in R^P, x_n \in R^...
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1answer
146 views
How to find and calculate correlation in a data set which has category and continuous variables? [duplicate]
I am working on an Insurance domain use case to predict if an existing customer will buy a second insurance policy or not. I have a few personal details saved under different categories like Marital ...
1
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1answer
16 views
SGDClassifier partial_fit() for online learning - is one step of gradient descent enough?
I'm interested in incremental (online) learning for my logistic regression model trained with SGDClassifier. Basically updating the model as more labeled data comes ...
0
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1answer
28 views
Feature Importance based on a Logistic Regression Model
I was training a Logistic Regression model over a fairly large dataset with ~1000 columns.
I did apply scaling of features using MinMaxScaler.
I was wondering how to interpret the coefficients ...
0
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0answers
24 views
How do I get confidence intervals for an ElasticNet in sklearn?
I need to produce a row for the confidence interval for every field that I am calculating coefficients and scores off of. So here is my code so far-
...
0
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1answer
20 views
Cannot fig out error in my gradient function implementation in python
Im trying to implement following gradient descent function in Python for logistic regression:
$∇θ(−logL)=−X^T (y−e^{Xθ})$
This is my python implementation:
...
0
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0answers
85 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 ...
0
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1answer
42 views
Binary classification: is there a tradeoff between predicting class 1 vs 0?
I have been digging much more in detail into classification performance metrics lately to get my head around the 'dynamics' of classification algorithms. What I have noticed is that in binary ...
1
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0answers
34 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 ...
0
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2answers
28 views
How to Keep Missing Values in Ordinal Logistic Regression
I’m using mord package in python to do ordinal logit regression (predict response to movie rating 1-5 stars).
One of my predictor variables is also ordinal but ...
0
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0answers
22 views
How to handle missing data in a logistic regression?
I am building a model to solve a binary classification task. So far, the input is low dimensional (10 dimensions at most). I need to face the occurrences of missing input. It is my first time at ...
2
votes
1answer
54 views
Help in understanding the maths behind Logistic Regression
I am following the lecture notes available https://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch12.pdf
I cannot understand how Eqs 12.4 and 12.5 come,
why the Bernoulli probability has $1-p(x)$ in ...
0
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1answer
31 views
KNN scoring low compared to Logistic regression in MNIST challenge
KNN gives me a score of 0.76100 while it shows 94% accuracy for my training data (splitted with test_size =0.3) in my jupyter notebook while logistic regression gives me a score of 0.91485 with an ...
