Questions tagged [logistic-regression]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
354
questions
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Precision score (classification_report) 1/0 not predicting for 0 in logistic modeling using Sklearn [on hold]
I have a binary outcome for an imported CSV file I am working with. I used the sklearn library to use the logistic model to gather predictions for my target value and also generate probabilities. ...
0
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0answers
7 views
High accuracy in one v. all, lower accuracy in all vs. all
I am training a classifier (similar to logistic regression) on MNIST. I have 10 one -vs.-all classifiers for each number, each of which independently achieves >90% test set accuracy. However, when I ...
0
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1answer
17 views
How does the given data gets plotted on a graph
I come from a programming background and learning the math behind the data science and algorithms now.
I would like to understand the logic behind how a data gets plotted in a graph when using ...
2
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3answers
64 views
+50
References for longitudinal data analysis
So my goal is to study longitudinal data (data in time series) by applying some data mining techniques. Ultimately I want to be able to "predict" outcomes. For example, a study of patients along the ...
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2answers
28 views
How to improve accuracy beyond optimal level? [on hold]
This may sound like an impossible task, but I believe it's possible in many cases.
I have a tabular data set, with 341 columns representing independent predictor variables, and one column with the ...
1
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0answers
14 views
How does a simple logistic regression model achieve a 92% classification accuracy on MNIST?
Even though all the images in the MNIST dataset are centered, with a similar scale, and face up with no rotations, they have a significant handwriting variation that puzzles me how a linear model ...
1
vote
1answer
19 views
Accuracy noise patterns during model training
I'm training a logistic regression model on a small dataset. I have about 1300 samples that I split into a training and a testing set (70% and 30% respectively).
The training seems ok, however when I ...
0
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1answer
18 views
Why the Logistic regression model trained with tensorflow performed so poor
I trained a logistic regression model with tensorflow but the accuracy of the model was so poor (accuracy = 0.68). The model was trained using simulated dataset and the result should be very good. is ...
1
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1answer
29 views
Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?
I am using raw data set with 4 feature variables to do a Binominal Classification using Logistic Regression Algorithm.
I made sure that the class counts are balanced. i.e., an equal number of ...
0
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0answers
24 views
Linear/Logistic Regression for unknown values or how to get a good prior for new coefficients
Suppose, we model the probability of making holidays by country and town. The input data are people and how many people actually made holiday in that particular town:
...
1
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1answer
61 views
How to interpret Logistic regression coefficients using scikit learn
I have created a model using Logistic regression with 21 features, most of which is binary. I created these features using get_dummies. Few of the other features are numeric. I get a very good ...
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0answers
14 views
How do classification algorithms assign coefficients or importance to a categorical feature
I have a binary classification dataset with target variable being response (Y/N) and one of the predictor variable is month. Image has data on respondents count and rate by month (sorted by ...
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9 views
0
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1answer
32 views
What do we learn from training a dataset for logistic regression
What do we learn from training our dataset in Logistic Resgression?
Like in Linear Regression, with the help of training set we are able to generate a best fit line(y = mx+c) where m and c come from ...
3
votes
2answers
48 views
Which classifier performs better when using 'class_weight'?
I have used the 'class_weight' method to balance my multi-class classification problem, using Logistic Regression, Random Forest, and XGBoost classifiers. Among these three methods, logistic ...
0
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1answer
24 views
Calculating Univariate and MultiVariate Logistic Regression with Python
I have a simple data set of a number of variables and a single binary dependent variable. The data is stored in a data frame. When I use python's statsmodels.api and logit.fit() on the dataframe I ...
6
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1answer
58 views
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2answers
79 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 ...
0
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0answers
10 views
Ideas to derive new column or eliminate a column for Logistic Regression problem related to binary classification
I am working on a Logistic Regression problem to identify the leads that result into a student conversion for candidature. I have 2 columns in the dataset 'Last Activity' and 'Last Notable Activity' ...
1
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1answer
23 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 ...
0
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2answers
30 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 -
...
1
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1answer
24 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 ...
0
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0answers
9 views
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 $...
0
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2answers
53 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 ...
2
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1answer
29 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 ...
0
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0answers
15 views
What type of regression to use when modeling the relationship between a continuous variable and a discrete?
I'd like to create a regression model to find the marginal effect between usage (a rate from 0 - 100%) and tap-distance (1,2,3,4...). I'm working to find how a change in tap-distance to a feature will ...
1
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1answer
23 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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0answers
22 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 ...
1
vote
1answer
51 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 ...
1
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2answers
75 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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0answers
20 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 :
...
0
votes
2answers
18 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 ...
1
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0answers
13 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 ...
0
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1answer
29 views
1
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2answers
45 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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0answers
28 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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0answers
9 views
Strategy for unrecorded predictors
I'm trying to create a logistic regression model for predicting future admissions based on historic clinical/utilization/demographic information. Although I have three years history available, for ...
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0answers
29 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 ...
0
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0answers
15 views
Looping over multiple dataframes
I have 3 sets of data that I would like to run a logisitcs regression on and then add the results to the corresponding dataframes. i.e. X1 & y1 predicted results added to df1 on so on.
I've tried ...
2
votes
2answers
56 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 ...
0
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0answers
32 views
How to Compute Logistic Regression Cost Function?
I'm using MATLAB to calculate the Logistic Regression Cost Function, and I don't get the expected output when I test my code. My steps all seem to be logically correct. Can anyone please help me fix ...
0
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0answers
10 views
How to check performance of a model on a test set?
I have transformed my training set (predictor variables) using step_YeoJohnson for satisfying the assumptions of model. But now how do I run my model on test set which is not transformed and has ...
1
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1answer
56 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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0answers
35 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 ...
0
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0answers
17 views
Build model to get daily probability of meeting a certain end of period goal
I was hoping for some consultation and direction with how to go about the following:
To give context, I work for an agency that manages advertisements on social media for general motors - ...
2
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3answers
71 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 ...
0
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1answer
17 views
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 ...
2
votes
2answers
84 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/...
0
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1answer
84 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}
...
1
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1answer
18 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 ...
