All Questions
Tagged with imbalanced-data classification
53 questions
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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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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 ...
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29
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Questions of handling imbalance dataset classification
I am trying to predict number of members who will discontinue their membership. The whole dataset is about 12 millions rows of data with about 40 columns. A member status can be “Continue”, “Voluntary ...
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Generate synthetic data for majority and minority classes
I am working on a classification problem where I try to generate synthetic data for both the Majority and Minority classes,as i want to train my model on synthetic data and test on actual data, i am ...
- 161
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3
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587
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Optimize metrics for Fraud Detection Imbalanced Data
I would need your help to improve my model performance. As mostly happens for fraud detection, I have an imbalanced dataset (0.1/0.9). I would like to optimize the recall for my target 1 and 0, ...
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How to choose the best technique for handling imbalanced data for binary classification?
I am working on my thesis on imbalanced dataset for binary classification problem. I need to handle the imbalance on data before make the classification, but I am not sure what technique is better to ...
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How to Handle Imbalanced Data in a Classification Problem?
I am working on a binary classification problem using machine learning, where my target classes are imbalanced. I have approximately 80% of data points in Class A and only 20% in Class B.
I have tried ...
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Sample Size Inconsistency Error with imblearn's classification_report_imbalanced
I'm encountering an error when using classification_report_imbalanced from imblearn.metrics on a classification task. The code runs smoothly until I add the classification_report_imbalanced function, ...
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105
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Are mlr3 class weights applied to validation score calculations?
I have previously used mlr3 for imbalanced classification problems, and used PipeOpClassWeights to apply class weights to learners during training. This pipe op adds a column of observation weights to ...
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119
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Using Class_weights for imbalance dataset in Mask RCNN
I have added Class_Weights to be used while training Mask RCNN on custome dataset. It is showing error :
ValueError: Unknown entries in class_weight dictionary: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ...
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51
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Error in checkMeasures(measures, learner) : object 'fbeta' not found
I am doing an imbalanced classification task, so I want to use f-beta as performance measure. I used the library(mlr) to set measures=fbeta, which follows:
library(mlr)
#create tasks
## Create ...
- 926
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338
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There were missing values in resampled performance measures
I need to do a classification task on this dataset. As the following code shows, I tried to implement xgboost using caret package. Since my dataset is imbalanced, I prefer to use Fscore as performance ...
- 926
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238
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WeightedRandomSampler with multi-dimensional batch
I'm working on a classification problem (100 classes) and my dataset has a huge class imbalance. To tackle this, I'm considering using torch's WeightedRandomSampler to oversample the minority class. I ...
- 108
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1
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406
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Poorly calibrated probabilities but good classification in confusion matrix
I have an imbalanced data set. My goal is to balance sensitivity and specificity via the confusion matrix. I used glmnet in r with class weights. The model does well at balancing the sensitivity/...
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243
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Undersampling/Oversampling issues with onehotencoded categorical data
I am trying to fit a classification problem which has a (40000 vs 400) split between 0 and 1 class. I am trying to play around with oversampling and undersampling (not preferred) but keep running into ...
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