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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88 views

Data quality improvement as a part of preprocessing: Imputation

I have a python pandas dataframe representing a superset. The data contains a lot of nulls which I want to overwrite with real values. the superset has: both numerical and categorical data some ...
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30 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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Predict multiple labels when labels are of mixed type: floating point and categorical

I was provided with a data file which looks like this: ...
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284 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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993 views

What is the better way to predict classes for the models developed using the functional API in Keras

We can predict the class for new data instances using the Sequential classification model in Keras using the predict_classes() function. What is the way to predict the class for models that developed ...
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34 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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36 views

Is it better to have one model with more categories or less with two for multi-label classification?

For classifying text into three classes question, complain and complements where each sample can have multi-labels (question and complains, question and complements): is it better to have one model ...
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2answers
57 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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21 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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175 views

Public dataset for news articles with their associated categories for multilabel data classification

I am wondering if there are any public datasets of news, like The New York Times (NYT) or similar to various news categories such as politics, entertainment, lifestyle, general news, sports, etc. I ...
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128 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, ...
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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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2answers
90 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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36 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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32 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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101 views

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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102 views

Trained CNN individually on multiple images to classify them, how can I now classify a related "set" of these images that correspond to one object?

I have a N object classification examples, each example consisting of a set M individual images of the object at different angles. I've trained M CNNs with the dataset of one particular image angle ...
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11 views

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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1k views

Multi Label Classification on Data Columns in Tables

I am seeking guidance on a machine learning problem involving the tagging of data columns. Currently, I have a system where users can add multiple tags to a columns in a table. However, I want to ...
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1answer
105 views

How to train on extended data set correctly

I have trained my classifier on pictures with a mixture of several classes on each picture, e.g. A-F. The classifier is able to (nearly) correctly segment those classes on the images. Now I got more ...
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1answer
1k views

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 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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1k views

Using LSTM for multi label classification

I am trying to use LSTMs to train and predict authors using reviews data and metadata ...
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17 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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1answer
14 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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1answer
52 views

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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119 views

Multi-label classification with nested features

I need to perform a multi-label classification. I have three features and they are nested. I am unsure how to combine this or what kind of classification algorithm would be best. Some multi level ...
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17 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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1answer
101 views

Reframing multilabel classification with imbalance in "both" directions

Consider the multilabel problem when asking "does the sample belong to this class" with, for example, a movie label dataset where almost every movie is labelled "drama" because of ...
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1answer
5k views

Keras stateful LSTM returns NaN for validation loss

I'm having some trouble interpreting what's going on in the training and validation loss, sensitivity, and specificity for my model. My validation sensitivity and specificity and loss are NaN, and I'm ...
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44 views

Ranked or Ordered Class Classification

My friend was asked this question in an interview for analytics and I cannot figure out the answer so I would like to see how could this data science problem be solved. Here's the problem: Let's say ...
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2answers
364 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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220 views

TensorFlow Time Series Tutorial Enhancement Gone Wrong

I’ve been following this time series tutorial for Tensorflow… https://www.tensorflow.org/tutorials/structured_data/time_series And it was going well and seemed to work ok. I substituted with my own ...
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8k views

How do you calculate Precision and Recall using a confusion matrix in Matlab?

I am working on a three class problem. How do you calculate precision, recall, f-score, and MCC for each class while using MATLAB? Here is my confusion matrix: ...
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1answer
45 views

Which is better: multi-output model or separate models for similar tasks?

I am working on two problems: classification of images into high-level classes (e.g. shoe, dress, jacket etc.) classification of the attributes of the same images on a lower level (e.g. shoe style, ...
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38 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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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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1answer
13 views

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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29 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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13 views

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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1answer
18 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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16 views

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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131 views

How can I annotate labels to images automatically?

I have 80 classes, for each class, there are 100 images. I want to label all images for object detection. For this task I have downloaded the LabelIMG tool but it's taking a long time to do it. How ...

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