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Questions tagged [multilabel]

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

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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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8 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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14 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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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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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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31 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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15 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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10 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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121 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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27 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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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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59 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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157 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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16 views

Bayesian prediction with minimum expected loss

I am studying for my machine learning exam and i have the following problem that i want to solve for preparation: I already solved Problem 1a, I have problems with 1b. After some google search I got ...
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In which situation different methods in multi-label classifications in scikit learn should be applied?

I have read this to learn about various method in multi-label classifiers. I learned that there are 3 techniques to do multi-label classifications: ...
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118 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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37 views

binary least square classification and labelling

I'm trying to do least square method on a set $X \in \mathbb{R}^{100 \times (2+1)}$ (the $+1$ is for the dummy bias feature) for a classification task on 2 classes (NB: no multiclass) and I found that ...
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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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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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20 views

what should be the default of the numbers in labels in multi label classification

I know my question is naive but I could not find a reason for the output I got. I am doing multi-label classification and I have 7 labels. I applied two different classifier. logisticRegression SVM ...
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123 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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19 views

Update Class Probabilities using a Bayesian Filter

I am classifying images over time in categories such as office, bathroom, living room and so on. The idea is to use all these classification to categorize the room where a robot is. I want to use a ...
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29 views

Assign labels on multi label classification

I have a multi class and multi label problem: each sample can be labelled with a number of labels between 1 and n out of N. So I train N binary classifiers, so that each of those can say if the ...
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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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134 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
451 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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22 views

How to classify multiple correct answers to a question when training QA model?

Let's assume the visual QA problem. On a given picture and a question: What's the weather like? there could be multiple correct answers like: bit cloudy, there is bit of sun, it's not raining and so ...
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265 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
57 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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95 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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80 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
111 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
342 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
756 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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215 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 ...
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1answer
211 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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386 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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2k 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
2k 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
221 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
4k 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
35 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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252 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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1answer
164 views

How to solve a multi-class and multi-label problem?

I have a following classification problem with somewhere around 2000 examples. For each example, there is a feature vector $\bf{x}$ of size $N$ and a label vector $\bf{y}$ of size $L$. Each label ...
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1answer
19k views

Why does keras binary_crossentropy loss function return wrong values? [closed]

Binary cross entropy for multi-label classification can be defined by the following loss function: $$-\frac{1}{N}\sum_{i=1}^N [y_i \log(\hat{y}_i)+(1-y_i) \log(1-\hat{y}_i)]$$ Why does keras ...
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1answer
385 views

Classifier accuracy decreases as n of n-gram models increases. Is this expected?

I am trying to tackle a multi-classification problem that requires text processing. The data contains a lot of samples (approximately 100.000 samples) and one of the features I need to work with is a ...
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222 views

achieving consistency between training/test target representations, in multilabel classification

TLDR: What is the best practice in multilabel classification to address the fact that the training and test sets probably won't have completely overlapping sets of labels, and how should I program ...
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1answer
43 views

Chance to belong to each of several classes

There is a project which I band my head on for some time and I'd like to hear if anyone of you faced such a task before and how they solve it: I'm thinking of using machine learning to show people ...