Questions tagged [multilabel]

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

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Metrics for Multilabel Classification

From what I've read, F1-score is a commonly used metric to assess the performance of a multilabel classification problem. However, I recently came across mAP@K and mAR@K as metrics used for ...
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13 views

Statistically compare two mutli label classifiers

I am trying to classify two different multi-label classifiers. Sample data: ...
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Multilabel Tweet Classification

I need some general advice and possible ideas. Problem statement goes like this -- We are given a tweet and we have to specify associated labels for it like generalized hate, support, oppose, ...
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Labeling Multi-class images

I don't know if this is the right platform to ask the following or not. I am working with Raster images (multispectral-optical satellite images) and I want to use machine learning/deep learning for ...
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39 views

Multi-class classification with prior knowledge of class similarity?

Backrounds I would like to build a model that predicts a month label $\mathbf{y}$ from a given set of features $\mathbf{X}$. Data structure is as follows. $\mathbf{X} : N_{samples} \times N_{features}...
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How can I put a multilabel decision tree into PMML format?

I am part of a team that is creating an app to accompany stroke patients through the recovery process. One component of this is creating an algorithm to suggest treatments based on certain clinical ...
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How to approach a multilabel classification problem where the proportions of the predicted labels matter?

My original task was to classify various cell types (the classes) based on gene expression patterns and this problem simply involves predicting one label from multiple classes. This was done easily ...
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20 views

How to get boundary points that are at interface of differnet classes in multilabel classification dataset

I am working on finding points which are at boundary of different classes. In other words finding points on which a classifier would be most confused or uncertain about. For a setting like multi label ...
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40 views

Ranking most probable labels from multilabel classifier

I have been working on a multilabel classification problem. I want to classify whether each of 25 labels is present on a given sample. The labels are not mutually exclusive. Ultimately, I would like ...
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Multilabel classification without using sklearn.multioutput.MultiOutputClassifier

Could someone recommend a tutorial that shows how to solve the multilabel classification problem, by using one-vs-rest approach, but not using sklearn.multioutput.MultiOutputClassifier. The ...
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Using pos_weight to improve recall in a multi-class multi-label problem

I have a multi-label classification problem, and so I’ve been using the Pytorch's BCEWithLogitsLoss. I’d like to optimize my model for a higher F2 score, and so want to bias it to have greater recall (...
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how do we find class conditional densities in a Multilabel data classification problem [closed]

i wanted to find distribution of class conditional densities in a Multi label data-set. Any source to learn Multi-Label Classification the Bayesian way
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Multi-label Text class

The data i am dealing with are simple text sentences that needs to be classified into variaous labels that correspond to the different topics as simple as Yes/No class. Several labels can be assigned ...
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DL Image Segmentation: examples without labels for every class

Background At my company we have a large dataset of pretty standard image segmentation data (image as input, multiple masks as labels) that we've curated ourselves. We've done so iteratively over the ...
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What is the difference between multi-class and multi-label classification? [duplicate]

What is the exact difference between multi-class and multi-label classification? For example, if you have a fridge with a camera that can view inside to see what products are still in stock, is this ...
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9 views

Methodologies for determining class labels

I am trying to figure out if there is a way to label data before training an ML algorithm with it. Problem: I am looking at a financial data set of certain securities, with a list of features ...
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22 views

categorical distribution in validation set

I have a dataset that contains 6877 samples. This is a multiclass multilabel classification which means that we have 9 classes and every sample can belong to one or more of these classes. The total ...
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Multiple ground truths in a multi-class classification

My dataset is comprised of individual images that three different users (A, B, C) have graded into three different labels (2=Pass, 1=Borderline, 0=Fail). Other features about the image are present as ...
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Imbalanced data in multi-label classification [duplicate]

I am trying to do MLC using the CnicalBERT pre-trained weights. The data is little biased i.e., some classes more frequently than others. After applying ML-ROS oversampling technique, Mean IRBl ...
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Can target encoding be performed on a mutli-label classification problem?

Is there a way to perform target encoding on multi label (closed set) problems, obviously target encoding is used on multi-class problems all the time, but i'm wondering if it works for multi label ...
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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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148 views

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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37 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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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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128 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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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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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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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
475 views

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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247 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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149 views

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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192 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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237 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
83 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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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
424 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
72 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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177 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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107 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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102 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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1answer
250 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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2k 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
139 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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1answer
605 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
704 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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32 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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1answer
557 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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195 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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273 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 ...