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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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Multivariate time series logistic regression [on hold]

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), age (0-35,35-55, >=55) ...
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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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Question about designing a multi input/output LSTM with different Tx, Ty [on hold]

I like to know if my Tx is 20 but I need a Ty of 3, how should I convert this input to that output? Or specifically, I must get my 3 preferred y^s from which units? the last 3 units(a<17>, a<18>,...
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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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1answer
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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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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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Business Specific Dataset for Business News Classification [migrated]

I need a multi-label training business news dataset that has rather detailed categories on what the news article is about. For example, in an article about BMW publishing their annual report, I'd ...
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1answer
33 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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ML algorithms for regression in the case of label noise with a known distribution?

I'm pretty new to machine learning, and I am interested in some ideas for algorithms or references for papers for using a ML algorithm for regression when the labeled data has label noise with a known ...
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Are there any open data sets for software clasification? [migrated]

I want to train a classifier that takes as input the description of a software installation and outputs tags based on categories that the new installation fits into. Are there any publicly available ...
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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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How to optimize multi-label classification with string input AND partial search matching

Need a way to optimize multi-label classification having a string(sentence) column as input and multiple categorical targets. The current implementation is taking all the strings and tokenizing them, ...
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How to Compute Multinomial Naive Bayes likelihood

I'm following this tutorial to implement a Multinomial Naive Bayes classifier to categorize text documents. It works to identify 1 single class, but how could I get the likelihood of a sample to be of ...
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Multi output decimal array for a single example m in tensorflow

So my training data looks like this: X_train.shape (395,385) Y_train.shape (395,384) In the above example: number of ...
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Weakly supervised learning and missing labels for data that likely contains that label

Cross-post from Cross Validated, because here seems more approperiate. 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 ...
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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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1answer
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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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1answer
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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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87 views

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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1answer
398 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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1answer
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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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1answer
123 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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2answers
104 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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2answers
158 views

Multi-label classification model in python?

Assume you have the following artificial dataset ...
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1answer
32 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
28 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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1answer
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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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1answer
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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
376 views

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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1answer
162 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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101 views

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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105 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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109 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. ...
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Multi-label classification, recall and precision increase but accuracy decrease, why?

I'm training a multi-label classification model using CNN, during training I'm using 90% of my data for training and the left apart 10% for validation, but something strange happens which is the ...
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1answer
70 views

Skills based recommendation system

Assuming that I have a list of Users with a list of skills: (each value is a different skill) And a list of Tasks with a list of demanded skills: Based on a manual classification that returned: (...
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1answer
53 views

Question classification

I have 10 classes and 10-15 questions in each class . Given a new question, I want to find the class to which the question is most similar?
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2answers
493 views

Where can I find freely available multi-label datasets online?

I'm trying to find multi-label classfication datasets, which are available for free online. By "multi-label" I mean that each instance can be labeled with anywhere from a single to $k$ labels, where ...
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1answer
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Sentence classification for chatbot

If I first classify an intent into classes using SVM classifier and then within those classes I classify that intent into subclass using another SVM classifier , will it be helpful or overall accuracy ...
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1answer
79 views

Object Detection classification

I am currently training a classifier for detecting resistors using TensorFlow Object Detection API. For that, I downloaded resistor images from ImageNet and I am currently labeling those who will be ...
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26 views

Decision Tree problem with dynamic loss function

I have a marketing problem, we have service lines, and margin on each line. For lines that disconnect and lines that do not, we want to identify features that help us maximize the difference between ...
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1answer
143 views

Is it bad practice to use multi-class over multi-label classification?

I have a multi-label classification problem-- millions of records that potentially could hold more than one label. I'm running into issues related to lack of research/examples online, and am unable to ...