All Questions
8 questions
1
vote
1
answer
24
views
Movement in cohorts
I am working on a user sales data which gets updated week over week. Based on the sales done in each week, the user is categorized in segment A, B or C. This means size of each segment could change ...
- 31
0
votes
0
answers
28
views
Which model to use for multitarget classification with strong class imbalance and many categorical variables?
I have a small dataset 79 observations in 21 variables.
Almost all the variables are categorical variables in the format yes/no or 1/2/3.
I would like to predict jointly three of these variables ...
0
votes
0
answers
178
views
The paradox of Imbalanced binary classification ¿To do something or to do nothing?
Context: Suppose we are interested in deploy a machine learning model to solve a problem of binary classification; furthermore, assume that the dataset $\mathcal{D}$ for the training of our model ...
- 143
2
votes
1
answer
50
views
Some questions about supervised learning, model evaluation and preprocessing [closed]
I've been trying to employ some basic techniques of supervised learning on a dataset that I have and I have several questions about the overall procedure (i.e. data preprocessing, model evaluation etc)...
- 123
8
votes
2
answers
110
views
Which classification algorithms are negatively affected by class imbalances?
I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
1
vote
1
answer
102
views
What are some possible reasons that your multiclass classifier is classifying alll the classes in a single class?
I have unbalanced classes.
Group1 N = 140
Group2 N = 35
Group3 N = 30
I ran the code on this data and all the Groups got classified as Group1.
I thought that since group1 is the majority group this ...
- 725
5
votes
1
answer
12k
views
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
3
votes
2
answers
3k
views
How to deal with classification problem where labels are non uniformly distributed?
I have a data set which has around 1000 samples and are divided in 4 groups - A, B ,C , D. The problem I am facing is that there are very high number of data sample which have B and C s output. They ...
