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Multi-label classification where multiple target labels might be assigned to each instance.

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Is skip-gram model of word embedding actually a multi-class task not a multi-label task, right?

So curious about this question, that I can't describe it in short. Please forgive me. Description： From multiclass and multilabel algorithms, we can get the definition of the multi-class and multi-...
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2answers
53 views

What type of multi-label method does sklearn's random forest classifier use? [closed]

I have trained RandomForestClassifier on data with 3 labels. The label set Y looks like this: ...
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1answer
15 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 ...
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1answer
63 views

multiple measurements for classification; which one to choose?

There are five different classes (labels) where the new points have to be classified at. For each new point, five different measurements are conducted, resulting into similar although different values ...
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37 views

Is Elmo equivalent to Fasttext+Bi-directional GRU?

From what I have read, Elmo uses bi-directional LSTM layers to give contextual embeddings for words in a sentence. So if I use a bi-directional LSTM/GRU layer over Fasttext representations of words, ...
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69 views

influence of oversampling on Semi-supervised multi-label learning

I have suggested a semi-supervised approach for the hierarchical multi-label classification task. I have included the MLSMOTE oversampling technique as a pre-processing step, and then evaluate the ...
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66 views

Label Switching and Pivot method

I am working on the so called label switching problem in Bayesian inference with Gaussian Mixture Models. To put in a nutshell, when your favourite MCMC samplers estimates the parameters of your GMM,...
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10 views

What is the best method using supervised learning to label images with single-pixel-level defining features?

The images are in later form of size 170 where each index could be a -1, 0, or 1. The images are multi-labeled, with 8 possible labels. The issue is that there are often only slight differences ...
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1answer
65 views

Optimising recall for multi-label classification?

I'm working on a multi-class multi-label classification problem where text (let's say comments on a website) should be assigned (possibly multiple) labels. There is a neutral (negative) class and ...
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19 views

Are these Multi-label document classification experiment steps sensible?

I plan to filter an input document using 4 different labels. Just for an example, a document discussing about movie summary needs to be labeled with 4 labels (Romance, Drama, Fiction, Hollywood). ...
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105 views

How to deal with an imbalanced dataset for multi-label classification?

You can consider me novice to intermediate at best with Machine Learning. For the past few months, I've been developing a neural network that learns to play a 3D fighting game by trying to mimic how ...
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2answers
60 views

how to build multiple independent binary logistic regression classifiers?

I have to build a logistic regression classifier to predict $\mathbf{y}$ given $\mathbf{x}$ where $\mathbf{x} \in \Re^{n}$ is an image and $\mathbf{y} \in \Re^{m}$ is a binary attribute vector (of $m$ ...
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20 views

How to call label encoding in multi-label case?

In the multi-label classification, one way to encode the data is to make a table with 1 row for each entry and one column for each label. For each entry/label pair, you get a 0 if the entry has the ...
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20 views

Machine Learning, which kind of classification should i use?

So im trying to make a ML classifier model to my data. My data has many X(variables [texts, integers, binaries etc.]) and 5 output(Y) information. In short, lets say i have 5 different places to put ...
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39 views

Transform a multiclass dataset into a multi-label one

I have a dataset of feature/label pairs. My labels are probabilities of each feature vector to belong to the K classes. Here is an example for K = 3: D1 = { (V0, [0.33,0.33,0.33]), (V1, [0.9,0.07,0....
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480 views

Multi-label classification with neural networks: Are correlations between class labels taken into account?

I am solving multi-label classification problem (assigning each image 1 to N labels) and want to use neural network (like in this post). Does this approach take correlations between class labels into ...
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1answer
254 views

Learn threshold for multi-label classification

I have a multi-label problem which I'm tackling with a NN. To get the multi-label scores, I use a tanh on the last layers (as suggested in the literature), and then selecting the ones corresponding to ...
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30 views

What methods exist for multi-output stratification (multi-label with different mutually exclusive label sets)?

To elaborate a bit: Methods do exist for single-output multi-label stratification (e.g., see scikit-multilearn). And there's a perfectly serviceable naive method for multi-class problems. The ...
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28 views

Weakly supervised learning and missing labels for data that likely contains that label

I would like to know how to deal with data that misses a label, but is likely to contain the label in a weakly supervised setting. Weakly supervised background Since labeling is a time consuming and ...
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355 views

How to use data_utils.WeightedRandomSampler and still be able shuffle training data in Pytorch?

I am working on the multi-label classification task in Pytorch and I have imbalanced data in my model, therefore I use data_utils.WeightedRandomSampler method ...
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13 views

What algorithm(s) should I use for a regression training and a classification prediction?

I am trying to work on a project on MALDI-TOF MS dataset. The dataset contains mass-spectrometry data of pure samples (1 bacterium species) and mixed samples (mixtures in known proportions of 2 ...
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48 views

Multilabel classification problem where a number of output labels are in certain range

I am tackling a multi-label classification task. In this problem, we have 13 classes For one sample $x \in R^{20}$, $2 \leq |h(x)| \leq4$ Here, $h(x)$ means the prediction labels of sample x by ...
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85 views

How to evaluate the results of a multilabel classifier using the predicted probabilities?

I can use sklearn accuracy_score to evaluate de predicted values of my multilabel classifier. But how can I evaluate the predicted probabilities obtained with predict_proba?
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1answer
188 views

Activation function when there are several output labels

If we had a NN to, let's say, clasify images of digits, but each image could contain more than 1 digit (all different), is there any problem in using a 10-dimensional output layer (representing digits ...
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1answer
384 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 ...
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1answer
25 views

Merge one label with one information for classification problem or multi-label classification

I want to build a model to support decision making in order to propose or not loan insurance to clients. Because sometimes clients asking loan and loan insurance have less chance to have their loan ...
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1answer
302 views

Choosing the number of labels in a multiclass classification problem

I've recently come accross a multilabel classification problem. Here, multiple labels can be simultaneously assigned to a single instance. I am interesting how one determines the number of labels to ...
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60 views

How to create an imbalanced dataset without leading to classifier overfitting

I am working on semi-supervised multi-label classification method that intrinscly deal with the imbalance problem, commonly present in multi-label datasets. That's why, i want to create an imbalanced ...
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120 views

PR curve and confusion matrix members for multiclass and multilabel classification problems [closed]

I am looking for any libraries which provide out of box support for calculating PR curve and the confusion matrix items(not just count but the items which contributed to the count as well) for ...
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1answer
180 views

how to limit one label while doing multi-label classification

I have a data set with 7 labels. I would like to apply multi-label classification on that. by that, each instance may have more than one label associated. now let's explain what I want. Rules in my ...
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40 views

Accuracy in multi-label classification [duplicate]

In a multi-label classification, the accuracy is commonly defined as [1] $$ \text{Accuracy}(\boldsymbol{Y},\, \boldsymbol{Z}) := \frac{1}{n} \sum_{i=1}^n \frac{\lvert Y_i \cap Z_i \rvert}{\lvert Y_i \...
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250 views

Measure agreement among experts in multi-label classification task

I was wondering whether there is a metric that can be used in order to compute the agreement, and therefore something like an upper bound for classifiers, among expert-labelled data. Assume there is ...
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1answer
620 views

multi label misclassification rates

I'm looking for a way to efficiently describe the performance of a multi-label classification model (if possible, something like confusion matrix for the multi-class classification). I'm not sure if ...
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339 views

Multi-label classification, binary loss concerns

I am solving a multi-label audio classification task with neural networks. The dataset is comprised of 10 classes, and the input data to the network are audio files where two of these classes are ...
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1answer
75 views

Neural Networks: How to do class prediction from murky labels

I'm conducting an experiment with the MNIST digit data - handwritten digits 0-9, each example composed of 28x28 bitmap of pixels. Imagine a collection of examples is drawn at random without class ...
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114 views

Multi-label classification with Neural networks

Task: Multi-label classification of sounds using neural networks. (Urbansound8K Dataset) Problem: How to best generate my combined dataset, considering maximum 2 sounds combined at the same time. ...
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120 views

Multi-label classification: overlapping or graph structure among labels

I am doing multi-label text classification. I have 5000 classes and there is a graph structure among these classes. How to deal with multi-label classification where there is overlapping or graph ...
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1answer
217 views

Best apparoaches for feature selection in multilabel classification

I have dataset which consists of around 46k observations and 20k features. The target vector is of length 75 (and so the target matrix is 46k x 75). among the features few are categorical and others ...
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1answer
551 views

Multilabel classifier Prediction using categorical cross entropy loss model

I am doing a multilabel classification using categorical cross entropy as the loss function. My input labels are a 1d vector of the form = [2 4 5..] First I convert my labels to categorical using, ...
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1answer
936 views

Loss function and activation function for categorical AND multi-label classification in neural network?

I am training a neural network to classify a set of objects into n-labels, each label with m different category. E.g. for n = 5, and m = 3, an example output is [0,2,0,2,1]. I can also transform the ...
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298 views

How to choose threshold in probabilistic multi-label classification?

My problem is to tag some texts with some labels. That is multi-label classification in ML. I did predict with Catboost classifier and get some results of binary ...
5
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1answer
270 views

Theoretical justification for training a multi-class classification model to be used for multi-label classification

Can a multi-class classification model be trained and used for multi-label classification, under any mathematical-theoretical guarantee? Imagine the following model, actually used in one machine ...
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425 views

What is a good loss function in multiclass multilabel classification where only one of the possible labels is observed?

I am training an ANN in multiclass multilabel scenario, where only one of the possible labels is observed at a time, let me illustrate on an example: I have a state X and the ground truth label Y for ...
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4k views

Confusion matrix for multilabel classification

I know that a similar subject was treated here, but my question is a little bit different. I have a result of multilabel classification, like this (2 observations, 3 labels in the example, in ...
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1answer
129 views

How to Deal with Categorical Variables that Allow Selection of Multiple Values per Observation?

Say you are dealing with a movie database that has movies and their genres. Genre is a categorical variable but each movie can belong to more than one genre. For example, Movie A may be Comedy and ...
5
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1answer
3k views

Multi-label or multi-class…or both?

I'm having a hard time getting the difference between multi-class and multi-label classification with CNNs. My understanding is that if I want to classify different breeds of dogs, that is a multi-...
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1answer
487 views

How does Binary Relevance work on multi-class multi-label problems?

I understand how binary relevance works on a multi-label dataset: the data is split up into L data sets, where L is the number of labels. Each subset has a column where either a 0 or a 1 is assigned ...
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1answer
5k views

Multilabel Classification with scikit-learn and Probabilities instead of Simple Labels

I'd like to classify a set of 3d images (MRI). There are 4 classes (i.e. grade of disease A, B, C, D) where the distinction between the 4 grades is not trivial, therefore the labels I have for the ...
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1answer
37 views

Relation between inputs and outputs

I have a problem which I do not know even if it is theoretically possible (not a ML expert): Assuming that there is a vector of drugs dosages that people take. So the input vector is something like (0....
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354 views

Label ranking in multi-label classification

In my multi-label classification task I'd like to provide label ranking for each prediction, i.e. the following classification result: (0.8, 'class A'), (0.2, 'class B') would mean that this ...

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