All Questions
Tagged with class-imbalance xgboost
28 questions
0
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1
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44
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Is there more to imbalanced classification with XGBoost than simply reweighting the loss function?
I am working on a dataset for fraud detection, which is naturally heavily imbalanced. My classifier is a class weighted XGBoost. In other words, I simply overweight the positive class by tweaking ...
0
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0
answers
58
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Improving Recall and Precision of the Minority Class with XGBoost to Maximize Profits in Unbalanced Data
The company is interested in identifying profitable customers who are likely to purchase a ticket when given a promotional offer. My goal is to build a model to predict whether a customer will buy a ...
- 1
0
votes
1
answer
638
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How to intrepret low F1 score and high AUC on training set?
I am currently working on a very imbalanced dataset:
24 million transactions (rows of data)
30,000 fraudulent transactions
(0.1% of total transactions)
and I am using XGBoost as the model to predict ...
1
vote
1
answer
307
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Need my xgboost model to be more liberal with classifications
I have an xgboost model that predicts the likelihood of a sales lead to close (actually to turn into an "opportunity" which is one step before the close but that's beside the point). The ...
- 113
1
vote
1
answer
3k
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scale_pos_weight effect in XGBClassifier
I can't find a satisfactory explanation about the effect of scale_pos_weight on an XGBClassifier.
It says everywhere to set it to Count of negatives / Count of ...
- 181
0
votes
1
answer
630
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ROC-AUC Imbalanced Data Score Interpretation
I have a binary response variable (label) 𝐵 in a dataset with around 50,000 observations.
The training set is somewhat imbalanced with, 𝐵𝑖=1 making up about 33% of the observation's and 𝐵𝑖=0 ...
- 21
7
votes
1
answer
3k
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Random Forest significantly outperforms XGBoost - problem or possible?
I have dataset of around 180k observations of 13 variables (mix of numerical and categorical features). It is binary classification problem, but classes are imbalanced (25:1 for negative ones). I ...
- 73
2
votes
2
answers
317
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Influence of imbalanced feature on prediction
I want to use XGB regression. the dataframe is coneptually similar to this table:
...
- 299
0
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0
answers
514
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XGBoost failing on highly imbalanced data!
I am working on a classification problem, where I am trying to predict a fraud login. The data is highly imbalanced i.e.
0 = non fraud logins , 1 = fraud logins
0 : 4538076
1 : 365
I have been trying ...
- 1
0
votes
0
answers
278
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Train/ Test split on small dataset along with SMOTE
I have a binary classification imbalanced dataset with 1000 samples ( 15% of class 1, 85% of the rest). My main goal is to build a robust classifier using the following approach. Wanted to know if ...
4
votes
2
answers
4k
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High Recall but too low Precision result in imbalanced data
I was training a model using XGBoost Classifier on a heavy imbalanced database with 232:1 of binary class. Because my training data contains 750k rows and 320 features (after doing many feature ...
- 73
0
votes
1
answer
2k
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Hypertune xgboost to dealing with imbalanced dataset
My training data has extremely class imbalanced {0:872525,1:3335} with 100 features. I use xgboost to build classification model with bayessian optimisation to hypertune the model in range
...
- 73
1
vote
1
answer
92
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Strong overfitting accompanying strong class imbalance
I'm training an xgboost binary classification model. The data I have is around 600k and positive is only 0.1% of it. I tried to use all overfitting prevention techniques xgboost has to offer (tune eta,...
- 111
0
votes
1
answer
87
views
XG Boost result interpretation for unbalanced datasets (Accuracy & AUCROC)
My dataset is of shape – 5621*8 (binary classification)
Label/target : Success (4324, 77 %) & Not success (1297, 23 %)
(success and Not success were been ...
- 165
2
votes
2
answers
1k
views
Main options on how to deal with imbalanced data
As far as I can tell, broadly speaking, there are three ways of dealing with binary imbalanced datasets:
Option 1:
Create k-fold Cross-Validation samples randomly (or even better create k-fold ...
- 21
1
vote
0
answers
113
views
Identifying possible data leakage
I am building a binary classification model for imbalanced dataset using XGBoost. I tuned the hyperparameters for four different models based on 2 training datasets and 2 optimization metrics.
Class ...
- 755
5
votes
1
answer
2k
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XGBoost multiclassification interpreting predicted probabilities
Let's consider an example. I have patient level data, their symptoms, reading from various medical tests. Based on that, I have built a binary classifier given patient data to classify if they are ...
1
vote
2
answers
625
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Weights for unbalanced classification
I'm working with an unbalanced classification problem, in which the target variable contains:
np.bincount(y_train)
array([151953, 13273])
i.e. ...
- 303
1
vote
1
answer
31
views
is there any rule to apply pca to the imbalance data? [closed]
Is there any rule to apply PCA to imbalanced data? (randomforest, xgboost)
I used multiclass imbalance data to pca
but the log-loss accuracy getting decrease
any theoritical background of this?
- 513
2
votes
2
answers
4k
views
Class Imbalance and Cost-Sensitive Learning XGBoost
I'm fairly new to data science and machine learning and have been trying to read a bit more on methods like boosting for one of the projects I am working on. The investigator on this project is ...
- 21
3
votes
0
answers
806
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Target mean encoding worse than ordinal encoding with GBDT ( XGBoost, CatBoost )
I have a dataset of 23k rows of an unbalanced dataset 85/15 ratio, 10 variables ( 9 of which are categorical ) , i'm using CatBoost and XGBoost for a binary classification.
I applied cv (5 iteration ...
- 2,094
1
vote
2
answers
115
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Determining threshold in an area with very few samples of positive label
I have a binary classification task where I want to either keep or discard samples. I have about a million samples, and about 1% should be kept. I want to discard as much as possible, but discarding ...
- 11
3
votes
0
answers
436
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Adjust class weights due to class imbalance and class importance Multi class classification XGBoost
With respect to this question and the answer given by @Esmailian, Would anyone be able to let me know if Class B has a higher importance or the positive class ( i.e. it needs to have a higher ...
- 153
5
votes
1
answer
12k
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What is the best way to deal with imbalanced data for XGBoost? [closed]
There are a lot of way to deal with class-imbalanced data like undersampling, oversampling, changing cost function etc.
https://machinelearningmastery.com/tactics-to-combat-imbalanced-classes-in-...
- 211
4
votes
1
answer
4k
views
How to set weights in multi-class classification in xgboost for imbalanced data?
From this post, I know you can set scale_pos_weight for an imbalanced dataset. However, for the multi-classification problem in the imbalanced dataset, I don't ...
2
votes
1
answer
1k
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scale_pos_weight Xgboost
My question is rather simple what does the parameter scale_pos_weight in xgboost do? I know typically it should be $\frac{sum(negative cases)}{sum(positive cases)}$.
Does it oversample the minority ...
- 378
3
votes
2
answers
2k
views
Improving classifier performances in R for imbalanced dataset
I have used an "adabag"(boosting + bagging) model on an imbalanced dataset (6% positive), I have tried to maximized the sensitivity while keeping the accuracy above 70% and the best results I got were:...
- 178
42
votes
6
answers
55k
views
Unbalanced multiclass data with XGBoost
I have 3 classes with this distribution:
Class 0: 0.1169
Class 1: 0.7668
Class 2: 0.1163
And I am using xgboost for ...
- 585