Episode #125 of the Stack Overflow podcast is here. We talk Tilde Club and mechanical keyboards. Listen now

Questions tagged [imbalanced-learn]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
0
votes
2answers
27 views

How to find whether a dataset is blanced or imbalanced?

I have few dataset to experiment classification(Multi-class). These datasets are about 400GB. I wanted to know whether the dataset is balanced or imbalanced. How to know that dataset is balance or ...
0
votes
1answer
23 views

How to Split And Resample Imbalanced Dataset Into Train, Validation and Test

I want to understand how to split the imbalanced data set with a binary target variable where 87% of the samples are negative and 13% of the samples are positive. Now, I know that you should always ...
1
vote
0answers
35 views

How to train regression models on imbalance dataset?

I am trying to train a regression model on the imbalance dataset. For example, the input features are vehicle_type, ...
0
votes
1answer
43 views

Evaluate imbalanced classification model on balanced testing sample

Why it would be too optimistic to compute presicion, recall and f1-score to evaluate a model trained for imbalanced classification on a balanced testing sample ?
0
votes
0answers
9 views

Shrink the training set during the learning process

Is there any way to change the size of the training set during the learning process? For example, let's say we have four classes (with their distribution): [A (90%), B (5%), C(2%), D(3%)]. Can we ...
1
vote
0answers
31 views

Binary classifier on imbalanced dataset yields weird PR curve

I have a dataset with ~6M points, 9 features and two classes. The minority class represents just under 2% of the data. The data is first divided into 100 batches and a different classifier is trained ...
1
vote
1answer
44 views

Difference between sklearn make_pipeline and imblearn make_pipeline

Can anybody please explain the difference between sklearn.pipeline.make_pipline and imblearn.pipeline.make_pipline.
1
vote
2answers
37 views

Can we specify the number of data generated(minority class) using SMOTE?

I am trying to improve classification of imbalanced dataset creditcard fraud using SMOTE imbalanced_learn. But, in this it generates the data to 50%, can we give a specific number for the data to be ...
0
votes
1answer
64 views

Positively skewed target label in regression

I have a dataset where the target label is positively skewed and produces a long tail, and currently I have a high residual on these values when experimenting with some linear, tree-based and neural-...
1
vote
0answers
38 views

SMOTE and oversampling with constraints

I'm trying to apply SMOTE to a dataset that has time-constraints. I have information about users visiting a website. For some features, there are time constraints, e.g having the first visit and the ...
0
votes
2answers
47 views

A robust metric in the presence of class imbalance

When evaluating the performance of a multiclass classification problem, on a highly imbalanced dataset, what is the most robust metric for this purpose? I read a paper that states: "Average ...
0
votes
1answer
72 views

Best metric in imbalanced classification for multi-label classification

My test data are imbalanced, i tried to use the precision or the gmean as metrics for a multi-label learning model, but both metrics are not very informative. Is there any way to use for example the ...
0
votes
2answers
65 views

Dealing with the test set of imbalanced data

I am working on a problem dealing with unbalanced data that has a very specific request. I would like to know the following: When I have an imbalanced dataset and I do train test split, the test ...
1
vote
1answer
175 views

Improving accuracy on highly imbalanced dataset

I need some suggestions to improve my model accuracy. The training data shape is : (166573, 14) It has all int and float columns. I have dropped claims_daysaway column as most of values are NaN and ...
1
vote
1answer
298 views

Multi class Imbalanced datasets under-sampling imblearn

I have an imbalanced dataset. I am looking to under-sample. Even though, the oversampling process takes less time, the model training takes a lot of time. I have taken a look at imbalanced-learn ...
0
votes
0answers
50 views

Deep learning(MLP) on multiclass classification. Model learns only one class

I am new to deep learning. I have imbalanced class data. I used one hot encoding and scaling to preprocess my data. I have used adamoptimizer as optimizer function and sparse categorical crossentropy ...
2
votes
3answers
460 views

imbalanced dataset in text classififaction

I have a data set collected from Facebook consists of 10 class, each class have 2500 posts, but when count number of unique words in each class, they has different count as shown in the figure Is ...
2
votes
0answers
335 views

How to use SMOTENC inside the Pipeline?

I would greatly appreciate if you could let me know how to use SMOTENC. I wrote: ...