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Questions tagged [multilabel-classification]

Multilabel classification assigns to each sample a set of target labels. This can be thought as predicting properties of a data-point that are not mutually exclusive, such as topics that are relevant for a document. A text might be about any of religion, politics, finance or education at the same time or none of these.

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What's the difference between multi label classification and fuzzy classification?

Is it just the between academics and practitioners in term usage? Or is theoretical difference of how we consider each sample: as belonging to multiple classes at once or to one fuzzy class? Or ...
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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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DecisionTreeClassifier for multi label classification giving outputs as single classes

I have built a DecisionTreeClassifier for multi-label classification with details given on https://scikit-learn.org/stable/modules/multiclass.html with input data in shape ...
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Can an output class be defaulted?

In my use-case of multi-class classification, my data distribution is like below: It might be too silly to ask this (and possibly could be gravely wrong), but is there a provision to default an o/p ...
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Clustering of multi-label data

The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects. For the moment, for simplicity sake, each label can be marked as either true or false (...
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Multi-label text classification (3 targetted result columns)

I am trying to build a multi-label text classifier for suggesting "AC_location", "Issue" and "Part_Affected" on the generated events. The textual data is full of ...
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Multi-class classification as a hypothesis testing problem

I'm diving into the logistic distribution and its applications in classification problem (see my old question for more details about my idea). As discussed in my old post, logistic regression, in ...
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Multilabel classifcation in sklearn with soft (fuzzy) labels

I have a model which is trained in sklearn on a 5-way classification problem, which performs relatively well (there are kNN and SVM versions, and both reproduce a test set with high accuracy). When ...
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How to deal with classification where all target classes are independent (keras & image recognition)

Ultimately, I want to get a probability for each class for each observation. All of the classes are independent of each other so an image can be classed as one, some, or all of the classes. I would ...
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Balancing XGboost still skews towards the majority class

I have unbalanced dataset for multiclass classification and I tried to use the class weights option in XGboost and the classifier still tends to favor the majority class. I am not sure if I need to ...
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What are some possible reasons that your multiclass classifier is classifying alll the classes in a single class?

I have unbalanced classes. Group1 N = 140 Group2 N = 35 Group3 N = 30 I ran the code on this data and all the Groups got classified as Group1. I thought that since group1 is the majority group this ...
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How to utilize user feedback due to miss-classification when correct class label is unknown?

Suppose we are developing an app which is supposed to predict a dog's breed by it's picture. We trained a classifier (in my case an MLP) using some dataset and shipped the app to users. Now suppose ...
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How mean and deviation come out with MNIST dataset?

I am a novice at the data science, and I notice some repository state the mean value and deviation in MNIST dataset are ...
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Confusion matrix in multilabel classification of an object in more than one class simultaneously

Regarding a classification problem where for example given an image which depicts a human and we are trying to predict their stance and their behavior. For example Human 1: 'Sitting' and 'Eating' in ...
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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: ...
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LSTM RNN application [closed]

I am a newbie to machine learning. I am figuring out a way to predict student outcomes (pass, fail, drop-out)using LSTM? I have attributes to take into account - gender (M/F), previous grades (Pass, ...
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Is there a way to cluster words based on how similarly they sound?

I have a list of words for a fictional world I've made (don't judge lol). My ultimate goal is to generate more words that sound like them through a markov generator, but for now, I'm trying to build ...
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Tool For Multi-Label Image Classification

I am currently working on a project that requires multi-label image classification. The best way to achieve this seems to be through Binary Relevance. I was intending to use a convolutional neural ...
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Multioutput classification in Keras - how to get multivariate probabilities and deal with unseen classes

I'm struggling to design in Keras a deep neural network for multioutput classification model. The network works in tandem with external logic in a kind of feedback loop: in each iteration the external ...
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How to use sklearn train_test_split to stratify data for multi-label classification?

I am attempting to mirror a machine learning program by Ahmed Besbes, but scaled up for multi-label classification. It seems that any attempt to stratify the data returns the following error: ...
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how to label a tain_data? [closed]

I have one assignment that I have four files 1) train_data.csv: The training file contains two fields (text, id). 2) train_label.csv: The label file contains two fields (id, label). 3) test_data.csv: ...
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132 views

Keras decision threshold for Multiple Label prediction

I'm training a Neural Network to predict multiple labels for a given input. My input is a 200 sized vector of integers and the output should be a boolean vector of size 28. My ...
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1answer
57 views

Multi-label classification for text messages (convert text to numeric vector)

Given a dataset of messages which are labeled with 20 features, I want to predict the value of each feature for a new message. Dataset example: ...
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37 views

Transform single-label data set into multi-label data set

I received a data set containing a string of text and a label that categorizes that text into one of 50 categories. I'm hoping to build a model that predicts which category a string of text belongs in....
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Why does averaging a sentence's worth of word vectors work?

I am working on a text classification problem using r8-train-all-terms.txt, r8-test-all-terms.txt from https://www.cs.umb.edu/~smimarog/textmining/datasets/. The goal is to predict the label using a ...
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Unbalanced multi-label multi-class classification

What are common approaches in order to deal with unbalanced multi-label multi-class classification problems in deep learning? Furthermore there is correlation between the labels. I tried two ...
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Multilabel Classification With Ranking

I have a dataset as below: ...
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Pre training for multi label classification

I have to pre train a model in order to do transfer learning or fine tuning in multi label classification. I'm pretraining with cifar10 dataset and I wonder if I have to use for the pre training '...
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Multiple classification algorithms are predicting always exactly with the same scores. Is that normal? If not, what should I suspect?

I have been working on a multilabel classification problem. I am using Python machine learning libraries to implement the classification algorithms. For the cross-validation, I am using repeated K-...
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Forcing a multi-label multi-class tree-based classifier to make more label predictions per document

I'm been experimenting with tree based classifiers for multi-label document classification. All the trees I've created, however, tend to predict only one or two labels per document. Whereas the ...
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Advice on what Machine Learning Algorithms to study for a Job to candidate matching algorithm

I have asked in a few places and this seems to get down voted for some reason. If this is not the place to ask this then some advice on how and where to ask it would be appreciated. I'm creating a ...
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692 views

Training multi-label classifier with unbalanced samples in Keras

I'm trying to train a keras model that takes in samples, let's say $x_i$ for sample $i$, and predicts multiple independent labels, $\hat{y}_{ij}$, such that $\hat{y}_{ij} = 1$ if the model predicts ...
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3answers
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Feasibility: train a model to learn how to extract data from documents

I am searching for an approach for solving the following problem: Given I have a large amount of printed and scanned documents. I am already able to detect text and the corresponding bounding boxes ...
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1answer
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Handle 50,000 classes in OneVsRestClassifier

I'm new to data science and NLP. I'm trying to solve a problem that is having 1 million rows and some 50,000 distinct classes. The dataset has some text column as a predictor and the other one is the ...
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100% classification accuracy

I am trying to perform a multi-class classification where the network is trained to classify objects into 3 categories: cars, pedestrians and miscellaneous. I am using the KITTI Dataset for car ...
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In handwritten digit recognition problem using logistic regression, what changes needed to add another class “Not a Digit”

In handwritten digit recognition problem using logistic regression, normal implementation would forcibly classify even a picture of dog or cat as a digit. To eliminate this, what changes are needed to ...
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202 views

Keras multi-label time-series classification considering time-series as an input image vector

I am trying to build a multi-class classifier using Keras. I am not quite sure I have implemented it correctly. Data is like this label time-series variables [0:25728} ...
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112 views

How to use Automated Labelling for documents? [closed]

Let's say I have been given 1000 documents and 6 labels from someone. My job is to label each of these 1000 documents into 1 of the 6 labels which are words not numbers. How can I automate or semi-...
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Multi-label classification model in python?

Assume you have the following artificial dataset ...
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1answer
57 views

Multi-Class Neural Networks | different features

This may be a wrong question or something so feel free to correct me :). I have been studying neural networks for weeks now. I came across the multi-class classification model that uses neural ...
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1answer
39 views

Binary classificaiton for weather data if its class 1 or class 0 alert

I am working on weather data and it has few features that are independent variables such as severity, severity_id, urgency_id etc ... Based on these values, I would like to classify alerts into class ...
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How to correctly perform data sampling for train/test split in multi-label dataset?

Problem statement I have a text multi-label classification dataset, and I've found a problem with the dataset sampling. I'm facing two different strategies. The first one consists in preprocessing ...
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How to visualize results/errors of multilabel classifiers?

For multiclass classification you would normally choose a confusion matrix to plot the error of predicted classes against the target classes. What is the best way to visualize errors of multilabel ...
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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
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Dealing with extreme values in softmax cross entropy?

I am dealing with numerical overflows and underflows with softmax and cross entropy function for multi-class classification using neural networks. Given logits, we can subtract the maximum logit for ...
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367 views

Classification models with multi-class allowed for each record

I am training a multi-class classification model. Each record can belong to one or more classes. (actually can I still call it a classification model? or should it ...
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Loss function for Hierarchical Multi-label classification

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels (e.g., a simple MLP branch inside a ...
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133 views

Reuters / RCV1 / RCV2 datasets

I am currently tackling a multi-label classification problem. Where can I find a benchmark comparison of model results using the datasets mentioned in the title? I am interested in other benchmarks, ...
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135 views

Oversampling for multi-class neural net

Does this make sense or do I have no idea what I'm doing? I want to train a model that takes a sentence and outputs a binary multi-class vector of size $K$ where each dimension is a question class. ...