Questions tagged [multilabel]

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

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12 views

Initial loss for a multi-label prediction problem

I have seen this: https://datascience.stackexchange.com/questions/18991/is-there-a-rule-of-thumb-for-the-initial-value-of-loss-function-in-a-cnn Since my question is more mathematical in nature, I ...
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SMOTE for multi-label classification

I have a dataset with 77 different labels. Each sample has one or more of these labels. I did some data analysis and found out that the dataset is highly imbalanced - there are a large number of ...
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13 views

Multilabel classification and regression on time-series data

I am trying to develop an LSTM network on a vehicle dataset I have obtained from my professor. The dataset in about vehicle driving in a roundabout. I have the following tasks to complete 1. Classify ...
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19 views

How to maximize subset accuracy for multilabel multiclass image classification

I working on multi-label multi-class image classification. I am using TensorFlow. Currently I am using sigmoid on output layer with binary_crossentrpy. Model is ...
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How to choose operation point from precision recall curves for multi-label classification

Is there a commonly accepted method for selecting an operating point for a multilabel classifier to optimize for each of these aggregate metrics: micro averaged recall at some minimal acceptable ...
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91 views

Multi label classification baseline model

I have a multi label image classification task with a large number of labels (7000) . I am using ImageDataGenerator to flow the dataset from a file. Before I start ...
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18 views

How to handle a big5 personality traits task

I have a dataset consists of N tweets annotated with the big 5 personality traits (extroverted, stable, ...
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8 views

Neural network embedding layers allowing multiple class-membership features

Is there a version of embedding layers for neural networks that allows for multiple class-membership features? Any frameworks that have implemented this? E.g. imagine we are trying to predict ...
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10 views

Good way to solve product recommendation

I need to recommend products based on top selling products for a given day in the past. The only independent variable is date which i can derive some information from such as weekday, month etc. The ...
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1answer
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F1-Score in a multilabel classification paper: is macro, weighted or micro F1-used?

I read this paper on a multilabel classification task. The authors evaluate their models on F1-Score but the do not mention if this is the macro, micro or weighted F1-Score. They only mention: We ...
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94 views

Interpreting hamming loss for multilabel classification

I have a multi label - multi class classifier that aims to predict the top 3 selling products out of 11 possible for a given day. Using scikit learn's OneVSRest with XgBoost as an estimator, the ...
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Why is softmax considered counter-intuitive for multi-label classification?

In the FB paper on Instagram multi-label classification (Exploring the Limits of Weakly Supervised Pretraining), the authors characterize as "counter-intuitive" their finding that softmax + ...
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153 views

When does multi-task learning make more sense than multi-label classification?

As part of writing a book on machine learning, I am creating an extreme multi-label stack overflow question tagger for thousands of tags with varying numbers of training examples and I’ve approached ...
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102 views

How to you label (caption) the table title? (for example:Tests of Between-Subjects Effects for One-way ANOVA)

How do you lable/caption a table under One-way ANOVA? Tests of Between-Subjects Effects for One-way ANOVA OR ...
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1answer
38 views

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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794 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
130 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
68 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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116 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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86 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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80 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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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
127 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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20 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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860 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
104 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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26 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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42 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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1answer
538 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
419 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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31 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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460 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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118 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
224 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
592 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
26 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
378 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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86 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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132 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
226 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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48 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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340 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
647 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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369 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
76 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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122 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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130 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
275 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
712 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, ...