Linked Questions

1
vote
0answers
917 views

Why would random forest perform bad on unbalanced class

There is a huge number of posts saying that an imbalanced classes are bad. And only half explains it in terms of recall-presicion scores, meaning that accuracy can be high but F1 score low. What I ...
1
vote
1answer
491 views

Calibration after up and downsampling

I am experimenting with different techniques to deal with imbalanced classes in a classification problem. I am comparing upsampling the minority class with downsampling the majority class. Furthermore ...
1
vote
0answers
337 views

Effects of class imbalance on nn batch training

Say I have a binary classification task, where the positive class (1) is only 1% of the whole data set. Intuitively I can understand why this could be bad for the classifier as the model may learn ...
1
vote
1answer
223 views

Imbalanced Test Data

I have an imbalanced (1:5) training and test set with only two classes and have oversampled the training set with SMOTE so that the class ratio is 1:1. The ML model gives values over 0.7 for accuracy, ...
1
vote
1answer
154 views

How to deal with a highly unbalanced classification problem?

I currently have data where there are 5 labels, 1,2,3,4,5 for my $Y$ variable and a set of associated predictors $X$. The problem is, I have around $10000$ observations with label $1$ and around ...
2
votes
0answers
223 views

How to work with unbalanced datasets in generalized Boosted Regression Models using gbm in r?

I'm using generalized boosted regression models to explore what is the contribution of 20 independent environmental variables (x1, x2, ...., x20) to the explanation of the variability of the dependent ...
1
vote
1answer
198 views

When to use stratified k-fold

According to a post on Analytics Vidhya: Having said that, if the train set does not adequately represent the entire population, then using a stratified k-fold might not be the best idea. In such ...
0
votes
1answer
104 views

oversampling in nested cross validation

Introduction I have a small mixed dataset consisting of continuous and categorical independent variables with a dichotomous dependant variable. I'm running various algorithms (neural networks, random ...
1
vote
0answers
167 views

balance_classes in H2O, but for regression? [closed]

I am training with deep learning for regression in H2O for R. My dataset is unbalanced (ie. not evenly distributed). There has been discussion on whether unbalanced datasets are an issue or not, with ...
1
vote
3answers
51 views

Machine Learning - How to Sample Test and Training Data for Rare Events

Suppose I have a data set with 1000 observations. I want to train and test a Classification Model to predict a target variable as true or false. However, in my observation set, true occurs only say 10%...
0
votes
0answers
135 views

Balanced LogLoss with XGBoost

Following the discussion on here I started worrying less about class imbalance. However, I recently started building a predictor, using XGBoost, and I wanted to used LogLoss as my target metric. I ...
1
vote
0answers
57 views

How do you deal with imbalanced data when you're doing regression?

To describe my problem. I'm predicting the price of an item depending on some text and other features in an ad. The training data contains a bunch of cheap items, some medium price items and few ...
0
votes
2answers
47 views

Population / Sample question

Today we started arguing at work, and couldn't come to conclusion. Let's say that we have a population of 1000 observations about various people. 50 of these people went bankrupt (1 - bankrupt, 0 - ...
0
votes
1answer
32 views

Dealing with dataset imbalance: test if adjusting is necessary

I'm currently working on a project which uses a imbalanced dataset (two classes) for training, and I'm not sure if I should do a resampling procedure or not. Is there a way to actually test if it's ...
0
votes
0answers
37 views

Training set target categories' distribution [duplicate]

In a book I'm reading I've come across the following quote: Accuracy on the test set is a good performance measure only when there is a relatively uniform distribution of target categories in the ...

15 30 50 per page