All Questions
Tagged with classification logistic-regression
121
questions
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23
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How to choose thresholds to discretize target for binary classification
My group is using logistic regression to investigate the most predictive features in a dataset. Our target variable is actually a continuous variable that we discretized using two cutoff thresholds (...
2
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0
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53
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Why is cross-entropy increasing with accuracy?
I'm making an implementation of the softmax regression and I'm struggling to understand the nature behind the problem of increasing value of Cross-Entropy: $H(y_i, p_i)=-\sum_{i=1}^C y_i log(p_i)$, ...
- 121
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76
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PySpark Logistic regression model weights are inconsistent between runs
I am training a pyspark logistic regression model using pyspark mllib. I am noticing that the weights are not being consistent in between runs. I have set the random seed in the training script and ...
0
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23
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How to estimate this variable in an MILP formulation
This is my first question being asked here. I've thought about different methods to do it, but to no avail. I want to estimate a variable that is either 0 or a positive number. Then I want to use this ...
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1
answer
2k
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How to calculate accuracy of a logistic regression?
A logistic regression involves a linear combination of features to predict the log-odds of a binary, yes/no-style event. That log-odds can then be transformed to a probability. If $\hat L_i$ is the ...
- 3,979
1
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1
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165
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Probability distribution of probabilities
We can get the prediction probabilities of a binary classifier from sklearn's API using the predict_proba method. Is it reasonable to expect that the shape of a histogram plotted for the prediction ...
- 11
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1
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130
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Quasi complete separation problem
I have some question related to quasi complete seperation problem on logistic regression algorithm.
So i run the model to predict credit risk and turns out it gave me good prediction score (AUC around ...
- 138
6
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1
answer
263
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Logistic Regression Modeling & Interpretation [closed]
I'm building a logistic regression model to predict the credit risk of lending company customers.
I'm using dataset from kaggle : https://www.kaggle.com/datasets/ranadeep/credit-risk-dataset/code
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- 138
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1
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52
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Can I use clustering after classification to improve the performance of my classifier?
Say I have a classifier that segments my feature vectors (e.g. representing applicants) into 3 distinct segments A, B, C by assigning each applicant a score between 0 (worst) and 1 (best) with e.g. a ...
- 101
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3
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961
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Tweak machine learning algorithm in SciKit to optimize for recall
I am given a dataset to detect fraud. Something similar like this:
https://www.kaggle.com/code/imgremlin/4th-place-in-fraud-detection-from-zindi
The issue with SciKit machine learning algorithm is ...
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1
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106
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How to find the optimal cut-off point to minimize both the FNR and FPR in R?
I should find the optimal threshold to minimize both the false positive rate and false negative rate. An equal weight between these two rates should be assumed. I write the following code:
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- 1,307
8
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1
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213
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Examples where simple classifier systems out-perform deep learning
I have been working on a problem where published results using deep learning are substantially worse than results I have obtained on the same task (using the same experimental protocol) using simple ...
- 561
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29
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Where do I draw the line at unbalanced datasets?
I have a problem where I am to construct a classification variable Yes/No based on another feature's value. We are interested in the Yes class in this case. I am told to use 10-fold cross validation.
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1
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116
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Spot Logistic Regression Training Error
My friend gave me this puzzle awhile ago and I've never figured it out.
...
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1
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46
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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 (...
