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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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Noob question - which NLP/deep learning technique shoud I use

Let's say I have dataset with inputs and expected outputs like this: ...
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How does dependency information impact binary classification in multi-label prediction models?

TL;DR: I don't understand the dependency issue with binary classification (binary relevance) compared to multi-label prediction models. I often read in papers that some kind of "dependency ...
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How to organize multi-layer data in Orange Data Mining?

I have data in the form of a MATLAB cell array in which: Rows are individual ROIs columns are image channels But each element of each column stores not only the mean intensity value of the ROI, but ...
DopeOmics's user avatar
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Multilabel Classification - Flat Binary Classifiers vs Hierarchical Binary Classifiers

Was researching on multi label classification to solve the problem of tagging news articles with topics and countries, where tags follow the syntax <topic>-<country>, and would like to ...
curious-24-7's user avatar
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What are approaches to identify the meaning of columns in a dataframe based on similarity to known column instances

In my domain we can perform upon to 12 tests on a substance, and record results for each of the tests at different pressures e.g. between 10 and 20 steps between 0 and 6000 psi. for each substance ...
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Loss increase while accuracy also increase [duplicate]

I'm training a fairly large classification model,and I'm having the below results. ...
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1 answer
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How to do a Multilabel classification where the label order is important?

I am doing carbon composite modelling for my college project. Each composite sample is created by stacking carbon fiber of different angles (0, 45, 90,-45). A sample can contain 8, 12 or 16 of such ...
apotheke's user avatar
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Is this classifier better than a random guess?

I'm working with the SAMHSA Mental Health Client-Level Dataset. I'm trying to train classifiers to predict the disorder given the rest of the columns. There are 14 binary disorder columns (bipolar, ...
Jackson Walters's user avatar
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How to create a multi label text classification model for small dataset in production [closed]

I have a multi-label text classification dataset which is very small around 80Kb, I am only going to receive a small amount of data for training from my client. But it is expected to build a high ...
Aayesha Qureshi's user avatar
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29 views

Variable length multi class multi label problem

I have to create a model that will output a variable number of tuples of size 3 as output. The tuples have to contain some category, not a float. I've never encountered a problem as this one so I'm ...
ptushev's user avatar
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Multinomial Logistic Regression sensitive to choice of Encoding

I am using the following LogisticRegression model using sklearn. The task requires to select one label from multi-labels, so if I provide a, b the output could be <...
user_04248753498's user avatar
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Object localization and text extraction using VGG

I'm new to Computer Vision and training a TensorFlow neural network using VGG16. The problem is quite simple: I'm training in a custom dataset to detect and localize numbers in a 100x100 image. The ...
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Academic name of dataset preparation method with hierarchical-learned labels? - E.g., cold→half-cooked→cooked

What's the name of the dataset preparation method indicating hierarchical ontologies? Assume photos of cold, half-cooked, and fully-cooked chickens. Annotate with temperature data. E.g., at current ...
Samuel Marks's user avatar
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LSTM Layer producing same outputs for different sequences

Currently I try to train on a multi-label language task with imbalanced class distribution. I have the following model, where I removed some of the feed forward layers to decrease factors in the chain ...
Thomas Christopher Davies's user avatar
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Custom loss function for multi label classification in catboost?

I have a data frame which I want to use for multi class classification problem. There are total 6 classes (say a, b, c, d, e, f). I want to improve the precision for three classes (say a, b, c) i.e. ...
SUNITA GUPTA's user avatar
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Is it possible to determine the probability of each time sample to belong a certain class using gaussian distribution with Recurrent Neural Networks?

I'm trying to train a deep learning model that predicts the probability of each time sample in a two-component time series . In this case, I want the target tensor (Y) to be a probability value for ...
Kevin Vargas's user avatar
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Fine-tune zero-shot classification model multi-label

I started a small project where I am trying to fine-tune a zero-shot classification model on a proprietary dataset. I was thinking to use the NLI approach, building contradiction and entailment ...
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How can I labelling a sequence of network traffic to one single classification?

I want to labelling network traffic (several .pcap-files) to different classifications. But this network traffic are not just one entry, there are sequence of entries (~50). So how is it possible, to ...
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How to Fix Dimension Issues of features and classes from a Multilabel Classification dataset in getting the Out-of-Bag Error of a Random Forest?

I have created a multilabel classification dataset using make_multilabel_classification from scikit learn: ...
Ralph Henry's user avatar
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How to deal with "Could not broadcast input array from shape (1141,2) into shape (1141,)" to get Out-of-Bag error while using Random Forest

I have a dataset that consists of 171 features and 39 labels. I captured both features and labels of the dataset through slicing: ...
Ralph Henry's user avatar
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Modeling Individual Device Demand in a Domestic Electrical Installation using Machine Learning

I'm working on a machine learning project aimed at classifying electrical loads detected in a domestic electrical installation by a current transformer (CT) during daily activities. The challenge lies ...
aldobranti's user avatar
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Training a two-layer neural network for multi-label data (binary bit array of dim 50)

This is my problem setup. Train Input size (6300x300) These are standard BERT embeddings, so floating point numbers, mostly negatives. Train Output size (6300x50) These are binary bit arrays like [0, ...
Niloy Talukder's user avatar
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21 views

Macro Averaging vs. Samples Averaging in multilabel classification problems

I am currently working on a multilabel classification problem and I have developed some models to solve it using the SciKit-Learn framework. I wish now to evaluated the models by producing scores for ...
user2566415's user avatar
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38 views

What is a good approach for classifying pairs of mutually dependent populations?

Imagine you have several pairs of populations - 1a and 1b, 2a and 2b, ... , na and nb. 'a' denotes a normal population and 'b' - an affected population. Populations 'a' and 'b' are mutually dependent ...
Hayes's user avatar
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Multilabel Image Classification - problem with probability at prediction

I'm building a multilabel image classification problem usinc MIMIC CXR dataset. I'm struggling with probability at prediction as for every image in test dataset the probability of an existance of ...
greg0001's user avatar
1 vote
1 answer
383 views

Multilabel classification: Choosing threshold

I'm creating a multilabel classification approach based on sentence embeddings applied to text taken from a chatbot. We have the following: a training dataset of 2,500 lines, where each line is a ...
LasiusMind's user avatar
1 vote
1 answer
35 views

How do I exploit partial labels for classification?

How does one learn a classifier from data that isn't always fully labelled? For example, say one has corrupted data from the CIFAR-10 dataset (which has labels like bird/automobile/ship/truck). Now ...
mister_mole's user avatar
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Existence of a "three-point" machine learning model?

I may want to ask if there are studies that exist which utilize a "three-point machine learning model. What I mean by "three-point machine learning model is that it may use several ...
Ralph Henry's user avatar
2 votes
1 answer
340 views

Multiple classes present in one-hot encoding

When dealing with classification for multiple classes present in the same sample, can the output layer have the form of one-hot encoding, but instead of only one hot, have multiple? That is, in case ...
smone's user avatar
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1 answer
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Movement in cohorts

I am working on a user sales data which gets updated week over week. Based on the sales done in each week, the user is categorized in segment A, B or C. This means size of each segment could change ...
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Large change in validation loss, small change in training loss

I'm training a multi-task, multi-label neural network. I am attempting to tune the architecture and am having some trouble interpreting the learning curves. Particularly, when I look at the learning ...
tensormoby's user avatar
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What statistical model suits for this problem?

I have a dataset with 6 target variables and the target variables are Boolean. The requirement is to use logistic regression to build the model. Which ML approach can be used in this situation? Will ...
Miuni Nihara's user avatar
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1 answer
366 views

Mulitlabel stratified k-fold splitting with non-overlapping groups

For multilabel stratification, we have a good solution implemented by scikit-multilearn which I believe is based on the algorithm presented in "On the Stratification of Multi-label Data". ...
tensormoby's user avatar
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1 answer
61 views

How to include information about labels in a multilabel classification task

Currently, I'm working on a multilabel classification problem for a shared task in NLP. I have quite a few labels, and with those labels, I have a little paragraph defining them. I was wondering if ...
ignacioct's user avatar
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1 answer
536 views

calculate sklearn metrics from 2d array

I have the following frame of actual value, ...
Ali A. Jalil's user avatar
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1 answer
69 views

Best approach for rule-based system in multilabel classification-problem?

I’m new to the world of NLP and am looking for some guidance. I want to create a rule-based system that “grades” text in accordance to some set of criteria. For example, one criteria could be “The ...
Incubu121's user avatar
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26 views

Which model to use for multitarget classification with strong class imbalance and many categorical variables?

I have a small dataset 79 observations in 21 variables. Almost all the variables are categorical variables in the format yes/no or 1/2/3. I would like to predict jointly three of these variables ...
Alberto De Benedittis's user avatar
1 vote
0 answers
95 views

How do I Classify text data with multiple sub labels? [closed]

If I have data that was like this How can I train keywords and try to classify them into these labels what was the best algorithm to try this and labels are not limited to 4 might increase and some ...
User1086's user avatar
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164 views

The paradox of Imbalanced binary classification ¿To do something or to do nothing?

Context: Suppose we are interested in deploy a machine learning model to solve a problem of binary classification; furthermore, assume that the dataset $\mathcal{D}$ for the training of our model ...
Ramiro Hum-Sah's user avatar
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1 answer
191 views

We pose recommendation as extreme multiclass classification problem, what is a class here? is it video category? or the video itself?

In the Youtube video recommendation paper, the author talks about candidate generation is a multi class classification problem, I am trying to understand what the classes here, a video category or the ...
Sandeep's user avatar
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1 answer
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What is the effect Cross-Multi-Labeling/Annotation on learning process?

I have a philosophical question regarding training convolution neuronal network. I am work on training NN for purpose of detection of Window and Window blind. This is an issue of cross labels; that is,...
Hesham Hendy's user avatar
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1 answer
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Beginner Question on Understanding Linear Classifier

I have been trying to understand the math behind Linear classifier for images and I'm hitting a roadblock to understanding this image below: I can to some extent agree that we stretch the pixels into ...
joesan's user avatar
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2 votes
0 answers
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Are more target labels in a multi-label classification always better?

Context We work on medical image segmentation. There are a lot of potential labels for one and the same region we segment. There can be different medically defined labels like anatomical regions, more ...
Spenhouet's user avatar
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1 vote
1 answer
1k views

Understanding SGD for Binary Cross-Entropy loss

I'm trying to describe mathematically how stochastic gradient descent could be used to minimize the binary cross entropy loss. The typical description of SGD is that I can find online is: $\theta = \...
Coinman's user avatar
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1 vote
1 answer
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Why is Word2vec regarded as a neural embedding?

In the skip-gram model, the probability that a word $w$ is part of the set of context words $\{w_o^{(i)}\}$ $(i= 1:m)$ where $m$ is the context window around the central word, is given by: $$p(w_o | ...
CMB's user avatar
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1 vote
1 answer
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Text to Text classification

I am new comer to the field of data science and have been struggling with a simple classification problem. It seems to be generic enough and I have a suspicion that there must be a better way to frame/...
ahc's user avatar
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1 vote
0 answers
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Methods for combining instance observations for classification

I am working on a project where I classify tiny moving particles into a few classes (fibers, hairs, glass shards, bubbles). The particles are only a few pixels large and are observed in a few frames ...
Simon van Eeden's user avatar
1 vote
0 answers
124 views

Method for multi-label category classification

I’m working on a project that involves a Natural Language Processing methodology. I want to classify categories(label) to biomedical news articles (it can be multi-label) (For example, News 1: ...
starry99's user avatar
3 votes
0 answers
41 views

Can we recognize different events in time-series data by patterns?

I'm currently have to deal with multiple time-series datasets with the same type of patterns. My quest is to find a way to label these data points (or may be intervals) correctly. Below is how the ...
duy quan duc's user avatar
1 vote
1 answer
26 views

Multi-label Classifier underperforms individual classifiers

I originally trained multiple individual binary classifiers for each label of an image. Then, I realized I can train a single multilabel model for this task. I used binary_cross_entropy loss for this ...
DankMasterDan's user avatar

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