Questions tagged [multi-class]

Multiclass classification is a classification task in which there are more than two classes. It is also called multinomial classification.

Filter by
Sorted by
Tagged with
0
votes
0answers
6 views

Why does multi-class classification using libsvm show a linear trend in the predicted categories?

I am adapting MATLAB code from a colleague's SVM pipeline to do eight-way classification on sets of EEG data, i.e. one prediction is made at each time point across the data, with each channel's ...
0
votes
0answers
13 views

How can I evaluate my multiclassification model using cumulative gain?

I want to run a model for multiclassification problem and I am only interested in the top x% results (recommendation model). I think using the ndcg@1000 evaluation metric is the best for this purpose, ...
13
votes
1answer
11k views
+50

Many binary classifiers vs. single multiclass classifier

What factors should be considered when determining whether to use multiple binary classifiers or a single multiclass classifier? For example, I'm building a model that does hand gesture ...
0
votes
0answers
9 views

Ranking prediction model by keyword

I have to predict rank(1~100) of online sales products. There are 'keyword' and 'date' columns, so each keyword and each date, there are 1~100 rank. And for X, there are 20 variables(review number, ...
0
votes
1answer
18 views

hyperparameter search with unknown test set distribution

I'm training a 3-class neural network classifier (conv layers and softmax at the end, nothing special). Let's say, in the test set I will have N1 examples of the 1st class, N2 examples of the 2nd ...
1
vote
0answers
20 views

Multi-Multi-Class Classification

I'd like to build a model that can output results for several multi-class classification problems at once. Suppose you have diagnostic data about a product that needs to be repaired and you want to ...
3
votes
0answers
50 views

What can I do when Overfitting doesn't seem to go away by any means?

So first of all I've seen a lot of overfitting questions around here, but none of the answers seem to improve my model. I wrote a neural network made without frameworks (only used numpy), and for the ...
0
votes
1answer
321 views

Improving Average F1 Score for Multiclass Classification

I'm trying to do a multiclass classification with h2o in R. I stacked a model with a RF, GBM and deeplearning. The accuracy is ok (~0.81), but the average F1 score is bad because class B has a very ...
1
vote
1answer
1k views

Cumulative Matching Characteristic (CMC) curve for multiclass setting

The CMC curve is supposed to be calculated for a gallery and a probe set, both sets of vectors identifying some person. What if I train a model on a closed set of say 10 people with 10 samples (e.g. ...
0
votes
0answers
4 views

Decision function to draw conclusion from two separate models

So I have trained two separate classifiers using sklearn's built-in Gradient Boosting Classifier. One of the classifier is responsible for classifying four classes(0, 1, 4, 6) while the other one is ...
0
votes
0answers
19 views

Increasing precision for one label in multiclass classification

I am doing multiclass classification for 3 labell with neural net. The model works fine but when I check precision/recall per label in validation set I can see that precision is a little bit too low ...
0
votes
1answer
237 views

Strategy to help classifiers cope with ambiguous examples

I have a machine learning problem where sometimes the training data will correctly have two or more similar/same training examples with different class labels. As an over-simplified example, let us ...
2
votes
3answers
360 views

Feature selection in multi class environment

I have a $\mathbb{R}^{10000 \times 25000}$ feature matrix (10000 observations and 25000 features). The observations come from 4 different classes, i.e. it is a multiclass classification problem. I ...
0
votes
0answers
9 views

Is this scenario a multi-task learning or a multi-label classification?

I would like to predict the Vehicle Descriptor Section (VDS) of Vehicle Identification Number (VIN) based on features like vehicle year, make, model, engine size, body type, etc. Expected output: A 5 ...
3
votes
2answers
71 views

MultiClass Classification - Training OvO and OvA

I like to know how OvO (One vs One) and OvA (One vs All) models are trained in multiclass classification problem. To keep it simple, we have 4 classes, each of which has 1000 datapoints. What are the ...
2
votes
0answers
31 views

Categorical cross-entropy vs Binary cross-entropy for multi-class classification with mixup

I understand that for multi-class classification the correct loss to use is categorical cross-entropy. However, when performing mixup as a regularisation technique two samples $(X_1, y_1)$ and $(X_2, ...
0
votes
1answer
34 views

What is the maximum Target cardinality in multi-label classification?

I have a dataset that consists of a target column with 65 classes. Also, the dataset has 200 columns/features. I researched multi-label classification and found the popular algorithms that can be used ...
0
votes
0answers
14 views

How to interpret high and similar ROC-AUC across models with slightly more marked differences in prAUC? (multiclass classification)

I am trying to compare the performance of different models for a multiclass classification task. The dataset itself has about 50 different categories with a lot of imbalance (the cardinalities of the ...
0
votes
1answer
198 views

Custom metrics for multiclass classification when class errors have different weights

I have a multiclass classification problem (eg. the target variable is made by 4 different outcomes: Product A, Product B, Product C and NO Product). Not all the errors are equal: for example, if the ...
0
votes
0answers
7 views

SMOTEBoost implementation

This question got to do with SMOTEBoost implementation found here but I believe the issue is relayed to imblearn library. I ...
0
votes
1answer
228 views

Should I develop a binary classifier or a multi-class classifier with my data?

I have a labeled set of data which contains 10 classes and ~400 training examples for each class. I would like to develop a classifier using this data. However, out of the 10 classes, I am only ...
0
votes
0answers
11 views

compare multi-classification models with different target length

I have a given classification task where I want to classify text based on top, and I also have a taxonomy of topics that looks like this: ...
0
votes
1answer
52 views

Multiclassification: precision-recall from scratch vs sklearn

I would like to know if there´s any issue behind using sklearn's precision/recall metric functions and coding up from scratch in ...
1
vote
1answer
23 views

Multiclass classification vs Binary classification with class merging: prediction accuracy

I have a dataset with 4 labels. For me the most important is to be able to distinguish label 1 from all other labels, I don't care that much about distinguishing between labels 2,3 and 4. The ...
2
votes
1answer
307 views

Machine Learning a Bijective Function

Is there any research on learning a bijective function from data? For example, let's imagine that we're trying to learn to assign four random musicians to instruments in a band. We have: lead ...
0
votes
0answers
20 views

Classification Problem using multiclass features input and ensemble methods

I am working on a classification problem. I am applying tree-ensemble methods (Histogram-Based Gradient Boosting and Random Forest) and evaluating premutation importance in order to understand ...
4
votes
2answers
5k views

multiclass classification having class imbalance with Gradient Boosting Classifier

I am using Abalon data for classification from UCI(https://archive.ics.uci.edu/ml/machine-learning-databases/abalone/abalone.data). I have scaled data and used TSNE for visualization. ...
0
votes
1answer
778 views

How to represent no-detection in a confusion matrix

So let's say we have a multi-class classification problem and we want to represent the outcomes as confusion matrix. All the examples I'm finding on the web asume that all the elements are detected. I ...
6
votes
1answer
7k views

Micro vs weighted F1 score

In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account? The main upside of choosing macro is that one gets a ...
1
vote
1answer
45 views

Multiclass classification metrics : average probability

I'm looking for a metric to evaluate my classification model. I have 3 differents class (0,1,2). And I want to get the average probability of the good label. For example, if my ml model get me those ...
1
vote
0answers
14 views

Improve Multiclass Classification by Binning weak classes?

I have a imbalanced Dataset with 23 classes from Accounting Data. My goal is to provide a suggestion to the accountant, which Account a Transaction belongs to. Gradient Boosting and any other Ensemble ...
1
vote
1answer
342 views

Mutual exclusive classes for deciding Softmax Regression vs. k Binary Classifiers

I realize that a similar question is asked here also, but my concern is related to the last section of this article from Stanford It says the decision will depend on mutual exclusivity of classes and ...
2
votes
1answer
174 views

Higher Test Scores but Higher Variance?

I am tuning hyper-parameters using 5-fold cross-validated grid search for various multiclass classifiers, and I keep running into the same issue that I can't quite wrap my head around. The hyper-...
0
votes
0answers
15 views

Can Transformer neural networks be used for botnet attack classification?

I would like to ask for some advice/guidance regarding a deep learning project we're working on, we're trying to do Feature analysis of IoT botnet attacks using Deep Learning we're working with the Nb-...
1
vote
1answer
221 views

Using FCNN for multi-class semantic segmentation trained on single class labeled image data

I am working on project where main task is semantic segmentation of land cover and another objects in Sentinel 2 multi-spectral images. Currently I posses dataset ...
0
votes
0answers
38 views

Weighting the loss function based on previous seen true positive rates

Similiar to class imbalance there is always something I would call "learnability imbalance" in multi-class classification. What I mean by that: Even when the classes are evenly distributed ...
3
votes
1answer
74 views

Accuracy always equal to recall

Fitting 3 different models on a 5-class imbalanced dataset. The results show model accuracy always being equal to the recall. How can this be possible? ...
0
votes
0answers
37 views

Treating an inherently multiclass problem as a two-class problem

I'm not an expert in this area, so if this question sounds a bit ill-informed, it is! I'm working on a problem somewhat akin to classifying birds with image data as input. Let's say for training data, ...
2
votes
1answer
1k views

How to manually balance unbalanced multi-class/multi-label data?

I have a multi-class and multi-label classification problem, i.e.: each sample can have more than one label associated to it and there is a total number of M ...
1
vote
1answer
1k views

LibSVM - Multi class classification with unbalanced data

I tried to play with libsvm and 3D descriptors in order to perform object recognition. So far I have 7 categories of objects and for each category I have its number of objects (and its pourcentage) : ...
0
votes
1answer
553 views

What's the purity of random clustering?

Purity is defined as $\mbox{purity}( \Omega,\mathbb{C} ) = \frac{1}{N} \sum_k \max_j \vert\omega_k \cap c_j\vert$ where $\Omega = \{ \omega_1, \omega_2, \ldots, \omega_K \}$is the set of clusters ...
0
votes
0answers
33 views

Why am I getting good accuracy but low prediction with Logistic Regression/KNN (Multiclass problem)

I am currently trying to solve a classification problem using machine learning algorithms. Code: https://colab.research.google.com/drive/1mcgxVT1GifYbCYjfWyCm94Z2Y_bQHRhA?usp=sharing Datasets: https://...
1
vote
2answers
1k views

Oversampling a multi-labeled data set

Given a data set where each individual data point can be assigned to more than 1 class (a multi-class, multi-label data set), are there any guidelines for calculating oversampling weights, i.e., the ...
0
votes
1answer
61 views

multiclass classification with weights vs competing risks with censored data

I want to fit a machine learning model to a dataset which is basically a survival analysis with competing risks with several failure types (e.g. mortality causes). However, I want optimal predictions ...
1
vote
1answer
30 views

Interpreting classification metrics for multiclass imbalance

I am at the point of reporting my results in a research article conducted. The dataset is highly imbalanced with class 1 and ...
1
vote
0answers
15 views

Problem with a dataset not being properly labelled

I have a labelled dataset but these classes are not perfect. Some classes should be combined into one, whilst others have too few data-points for training. My main concern is the former not the latter....
0
votes
1answer
232 views

For multiclass classification purpose I have to use a imbalanced dataset

I am facing a problem. It's a multiclass classification problem I have 5 categories A has 107 instances B has 101 instances C has 882 instances, D has 229 instances and E has 129 instances. I used Knn,...
0
votes
0answers
49 views

word embedding using Keras Embedding layer

I am learning using Keras Embedding layer to build embedding models. However, I failed to build a good embedding model. Can anyone help me check where I did wrong? Or not enough data to train? Data ...
2
votes
1answer
297 views

Why does the 'weighted' f1-score result in a score not between precision and recall?

On the F1 score sklearn page there's a section that explains each of the options for the average parameter. Under the weighted option, it says: "it can result in an F-score that is not between ...
2
votes
1answer
104 views

Metrics for multiclass classification model accuracy

Usually the last layer in multiclass classification models is a softmax, which is essentially a vector with elements the confidences for each class. The standard top-1 accuracy takes account only if ...

1
2 3 4 5
8