334 questions
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How can I apply SMOTE for multiple binary responses with NAs in R and produce a single balanced dataset? [migrated]
I have a dataset with several predictor variables and multiple binary response columns.
Each response is highly imbalanced (many more 0’s than 1’s) and also contains some NAs.
I am trying to balance ...
- 2,910
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67
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Loan Default Prediction - Kaggle
I am working on the loan default prediction data set available on Kaggle which has a highly skewed class distribution. The best model I have gotten so far is as follows using ExtraTreesClassifier:
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0
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1
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120
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Why is my BERT model producing NaN loss during training for multi-label classification on imbalanced data?
I’m running into a frustrating issue while training a BERT-based multi-label text classification model on an imbalanced dataset. After a few epochs, the training loss suddenly becomes NaN, and I can’t ...
- 26
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How to Build a Neural Network for Predicting Loan Status Using Multi-Table Data from the Berka Dataset
I am working on a project using the Berka dataset, and I want to build a neural network to predict the loan status for accounts. The dataset contains multiple tables, and I want to avoid flattening ...
-1
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1
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40
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Improving Accuracy [closed]
I am working on testing accuracy and performance using deep learning models on a complex dataset but I have reached a good accuracy but I need to improve it so any suggestions other than what I did(...
- 7
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87
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Use StratifiedGroupKFold with GridSearchCV in an XGBoost Model
Dataset: I have a very imbalanced binary dataset of Groups; approximately 362 "yes" Groups and 47000 "no" Groups. Each Group has time series data updated at minute intervals. For ...
- 33
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60
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Understanding the `model.fit` function in keras and imbalanced datasets
As an exercise, I'm trying to translate a model written in Keras (https://github.com/CVxTz/ECG_Heartbeat_Classification/blob/master/code/baseline_mitbih.py) into Pytorch code. I realize in Keras much ...
1
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2
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402
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Problem with Keras class weights and KeyError
I anticipate that I have seen the question: Keras class_weight error dictionary keys/values referring to the same problem, but the solution does not seem to help me.
With this code, where I just added ...
- 123
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265
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How to use skmultilearn.iterative_train_test_split to split to test, val and test?
The goal is to split an imbalanced dataset to train, val and test sets in order to train a multilabel model.
Following this simple example from HuggingFace and the documentation it is clear to me how ...
0
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27
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ROSE package in R not reading variable correctly; does not read updated value contained in variable
I'm hoping to receive some help here as I've struggled for a while now and I cannot figure out the problem.
I am using the ROSE package in R, attempting to make use of the function for random over/...
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64
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Imbalanced Dataset Correlation in Machine Learning
If there is an imbalanced dataset, I cannot figure out the correlation or dependency of the target column on different features. How can I check that?
I am using countplot but with that, I cannot ...
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195
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Managing problems of class imbalance in machine learning models using spatial data in R
I am trying to simultaneously perform feature selection and hyperparameter tuning on stacked learners (glmnet and rpart). However, I am encountering the following error message with the classif.glmnet ...
- 89
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0
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37
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I faced an error when I used PCA with LSTM model
I have a time series dataset with 20 classes, but they are imbalanced; when I tried a method like "RandomOverSampler", I got an error because of the 3D of our data so could you suggest a ...
0
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0
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65
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Weighted F1-score
I'm training and validating models for a binary classification problem in a dataset that has great class imbalance.
When searching for metrics for evaluating the performance of the models, I found ...
- 1
0
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0
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117
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Class imbalance calculation for each class in a dataset
I am trying to compute class imbalance in each dataset and my approach was to check average and standard deviation of the counts. The average is the total number of samples in class 1 / total number ...
- 41