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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26 views

A data in which an employee id is given in multiple months and many categorical features are there. To predict future retention. Recommend what to do?

I have this dataset in which we have to predict the retention of employees,i.e. how much will an employee stay in a company? This seems easy but the main obstruction here is that the same employee_id ...
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23 views

Error when trying to predict BERT model and obtaining classification report

I am following this tutorial about multi-label, multi-class classification using BERT. I am trying to get the predicted classification for y_pred, but when running ...
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27 views

Using sequences for multilabel classification

I have a sequential dataset of events, which looks like the following: ['some text here', 'more text here'] -> target Each datapoint is a true sequence ...
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28 views

under sampling the dataset of multi-label classifiction

I have a multi-label dataset, whose label distribution looks something like this, with label on x-axis and number of rows it occurs in the dataset in y-axis. ...
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28 views

Do I need a multilabel classification machine learning methodology or is it unnecessary?

Introduction I’m working on a social science research project that involves a Natural Language Processing methodology. I’m assigning multiple labels (For example, label 1: ...
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31 views

How to handle unclassifiable data in the dataset

Premise: Classification problem Input is three text fields Output classes are A, B, A&B (Note: A and B are not always exclusive though usually are, hence the 'A&B' class) Sci-Kit Learn is the ...
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41 views

Two-level (large category and small category) label classification problem

At present, there is an app classification task, the input is the function description of the app, and the two labels are the major category to which the app belongs and the small categories under the ...
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22 views

How to determine a good architecture for multilabel classification

I am working on an university project that requests us to classify Wikipedia abstracts about people by their professions. The output shall be a JSON file that assigns each Wikipedia abstract to a set ...
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135 views

What is the difference between LabelBinarizer and MultiLabelBinarizer?

I am trying to understand the difference between the two label encoding techniques for output variable. I have read things but still can't get a clear picture as what makes them different. Also can we ...
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112 views

train-tests split for extreme multilabel classification

I have an extreme multilabel dataset that contains thousands of labels, each label exists at least 10 times. What is the best way to split the data in a stratified way? I tried the ...
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15 views

Precision and Accuracy of a custom Object Detection Models usind networks from TensorFlow Model Zoo

I am trying to develop a model with three classes. To do so, I tried to develop a model with different combinations of the data samples in each class. For example: the $1^{st}$ model has 500 images ...
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41 views

OneVsRest Classification why do the probabilites sum to 1?

I am using OneVsRest Classifier in sklearn. So a multilabel model, 4 models for each class (i have 4 classes). When i called the predict_proba method i therefore get an array with 4 columns each one ...
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35 views

Shuffling data yields significantly worse performance

Edit: I've experimented a few times, shuffling the data at various steps. It seems that as long as I restart the python kernel and reset the dataframe indices, the performance is good. I'm still not ...
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change the value of the minimum of each row which satisfy condition

I have a tensor in which each row contains a value between 0 and 1. I am doing a multi-label classification and I change each value which is greater than 0.5 to 1 and else 0. (tensor > 0.5) The ...
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Ensemble/combining models weighted by number of observations?

Across a few different projects, I have hit a problem where I have two (or more) models: General-Purpose Model: A model which is based on a large amount of data not specifically relevant to my ...
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25 views

Multi-Label Regression of Categorical Probability Distribution that adds up to one

What would an ideal Tensorflow/Keras architecture look like, if the target is a multi-regression with values that add up to one? Toy Example: Tv Channels You work for a big TV-Station and your boss ...
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22 views

Searching for implementations of multilabel feature selection

Does anyone know of any packages that implement multilabel feature selection algorithms? There are many papers introducing algorithms, but few if any seem to be implemented publicly. I have been able ...
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19 views

LSTM or GRU for Time-series Multilabel classification

Univariate time series data with only one feature vector (e.g. 1x1300 as a time step), a superposition or sum of different signals, should be disaggregated or ...
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17 views

What are the options/best practices for encoding categorical features for multilabel classification?

I am working on a multilabel classification problem with both continuous and categorical features. For a single label problem, I might make use of a supervised encoder for my categorical features such ...
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18 views

What are the best ways to balance the classes in multilabel classification?

I have around 1000 rows of data with 9 labels. Each label can be either 1 or 0. Out of 9 labels I have 1 label which has 600 1s , 3 labels which have around 300 1s rest are having around 50 1s. I ...
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41 views

Predicting probabilities in Neural Networks

I have 1000 number of inputs in a sample each ranging between 0-1 as shown: ...
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20 views

How to figure out what elements are missing from a set, based on other sets?

I would like to solve a problem where I have a set of sets of possible values, but some elements of some sets are corrupted/deleted, so I had to figure out what is the most probable candidate ...
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Classifying visual environment in Tensorflow CNN (video analytics)

I am given a selection of videos of users exploring simulated 3D enviroments (kind of looks like the Sims video game) and I am tasked with being able to classify each room using a tensorflow framework....
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How to utilize the multilabel calssification labels during the course of training

I have a data set that consists of images. I am trying to perform multi-label classification on this data set. But the training labels consist of too many labels which are CSV file format. Now I find ...
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30 views

How many training data should I use in multilabel classification?

Now I'm using Keras to implement a multi-label classification model. Specifically, I want to classify who present in an audio clip (maximal 8 people). The label of data has 8-bit, for example, [0,1,0,...
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Error due to Colab RAM depletion when implementing Multi-label classification with BERT and Pytorch

Background: I'm implementing multi-label classification for tones (7 types of tones). Dataset shape: train_df=(5392, 8); val_df = (1348, 8) The modelling approach remains the same as this multi-label ...
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How to apply Helmert Coding in a real Machine Learning model?

My dataset is something like this ...
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19 views

train two models separately for multi-label classification

If we have a muli-label classification problem, is that true to train the model over each target separately? For example, if we have a 2-label(y1,y2) classification, once we train a model with y1 and ...
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Merging multiple classfiers

I am designing a classifier that takes as input features matrices of different dimensions, for example (Nx5, Nx10, Nx100, Nx1000) using visual bags of words of distinct dictionary sizes and methods (...
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351 views

How to perform Multi-Label Image Classification with EfficientNet

Problem My goal is to perform multi-label image classification with EfficientNet. It should take a picture as input and e.g. tell the user that it sees a person AND a dog on the picture, meaning the ...
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Predicted probabilities of Multi Label Classification

I'm currently working on a Kaggle Competition wich objective is to predict probabilities of an ID belonging to each class. There are 4 posible classes. The data is tabular and because it's a Kaggle '...
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Using a multi-headed neural network, how should I approach the regression head loss

I have a multi-headed NN where one head performs multi-label classification and the other a regression task on a set of images. The classification head outputs a one-hot vector where each value in the ...
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39 views

Data augmentation for tabular data in a multi label classification task

The task at hand is to predict the future lab values for a patient (1 if abnormal and 0 if normal) using the previous numerical data. It is a multi-label, multi-class time series classification task. ...
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75 views

Best Model for Multi-label image classification [closed]

Usually using CNN architecture with a Sigmoid function as an activation function in the last layer and using binary cross entropy can be used to output a probability for each class. However, the ...
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7 views

Class wise opinion for multi-label sentiment classification

I'm trying to build a model which separates positive and negative classes and assigns the label. I have a multi-label review dataset for example: No Review Label 1 Phone is good but charger is not ...
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34 views

Evaluating model with categorical target variables

I converted all the numeric target variables of MNIST dataset into categorical variables. So, 0 became zero, and so on. Next, I ...
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24 views

How do you perform multilabel classification that is also a multiclass problem?

I have a data set in which each row of data belongs to certain classes/labels. text class1 class2 class3 text1 pos neg na text2 na neg na text3 na neu na text4 pos neg neg text5 neg neg na ...
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53 views

Using softmax for multilabel classification (as per Facebook paper)

I came across this paper by some Facebook researchers where they found that using a softmax and CE loss function during training led to improved results over sigmoid + BCE. They do this by changing ...
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21 views

Stratification sampling of a json Array [closed]

I have a json array file that i need to create a smaller sample of for testing purposes. A sample of the file looks like: ...
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17 views

Not able to get a good accuracy score for the classification problem

I have taken a music popularity dataset which has five classes based on the popularity of the songs.I have made a Random forest model to predict the popularity of a given song(given its features).I ...
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1answer
195 views

Changing order of LabelEncoder() result

Assume I have a multi-class classification task. The labels are: Class 1 Class 2 Class 3 After LabelEncoder(), the labels are transformed into 0-1-2. My questions are: Do the labels have to start ...
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14 views

Feature vector representation

I have a clarification. I have to create a classification model for certain set of documents. We are supposed to flag it anamoly or not based on certain terms in the document. My question is the terms ...
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497 views

How to read the predicted label of a Neural Netowork with Cross Entropy Loss? Pytorch

I am using a neural network to predict the quality of the Red Wine dataset, available on UCI machine Learning, using Pytorch, and Cross Entropy Loss as loss function. This is my code: ...
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39 views

Best Way to tackle to time series classification problem?

I have a dataset where the input is a dataset for ICU patients where each ICU stay has 40 features (20 vitals, 20 lab values) and multiple time steps (the stays' length is between 6 and 19-time steps)....
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55 views

How to train BERT (multi label) on imbalanced dataset for search query category classification

I have a dataset of 2 million search queries relative to 7000 categories. same query could have multiple categories. Aim is to predict category/categories for query with confidence score. I tried ...
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38 views

How best to convert label classification into regression?

I have a dataset of genes for which I'm trying to predict genes that cause a disease. Originally I was doing this with a multilabel classification. I had 3 groups: I labeled already known disease-...
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88 views

Multi-label text classification. 3-4 labels per text, 100 labels overall

My first pet ML project, so please pardon if I phrase something incorrectly. Recently I had IMDB sentiment analysis binary classification practice on Tensorflow site. Now I am keen to do multiple ...
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36 views

Best algorithm/model to establish relevance between events utilizing mixed data type (Tags, Time, x_coordinate, y_coordinate)?

I'm building a relevance ranking system for incidents occurrence and prevention. My goal is to use four attributes to establish relevance: tag (About 500 tags), x_coordinate, y_coordinate and time. ...

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