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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SKLearn NearestCentroidClassifier score with predict_proba

I'm using the NearestCentroidClassifier combined with TF-IDF for classification of documents. The are linked to a growing number of document groups. I've set sklearns TfIdfVectorizer and the ...
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6 views

Using pos_weight with BCEWithLogitsLoss to improve recall in a multi-label problem

I have a multi-label classification problem, and so I’ve been using the Pytorch's BCEWithLogitsLoss. I’d like to optimize my model for a higher F2 score, and so want to bias it to have greater recall (...
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Random Forrest Sklearn gives different accuracy for different target label encoding with same input features

I'm using sklearn Random Forrest to train my model. With the same input features for the model I tried passing the target labels first with label_binarize to create one hot encodings of my target ...
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Doing q individual train/test splits for q possible labels in a multilabel problem?

Let's say that I have a multilabel problem, where each sample can be of class A, B, C, or any combination of these. Because of high imbalance, I've found that if I tackle the problem as 3 separate, ...
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19 views

Time Series Data Multi-Class Classification

This is a very general question, as I'm still very much in the learning phase with machine learning. I have some utility data around problematic meters. Even tho the data is "time series", I believe ...
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How to explain a stable NDCG@K in extreme multilabel recommender model

I am working in a multilabel recommender project and I try to evaluate it as a ranking problem. I calculate recall@k and precision@k which both looks quite well. Recall increases and Precision ...
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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 good, and seemed to work ok. I substituted with my ...
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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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Machine Learning - Multilable Text Classification

I am trying to solve a multilable text classification problem and used tf-idf for feature engineering and calibrated+linearSVC into the model. Results are great, however, I am trying to figure out a) ...
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136 views

ValueError: The number of classes has to be greater than one; got 1 class in MultiLabel Classification problem

I am working in Python in a Multilabel Classification problem. I have a dataset with texts and around 20k unique labels. I transformed the text to word embeddings and now I use that in a ...
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Time series multiclassification on process measured multiple times

I have been measuring the power usage of a 3D printer for a while. To create a dataset I've measured the power usage of the printer during different printing processes a few times. The data is ...
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21 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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Multiple Outputs LSTM

I am trying to create a neural network capable of classifying the type of music that a user normally listens to.The idea is that the neural network will receive a 2D input matrix. These matrix ...
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Text classification into thousands of classes

Could somebody point me to a paper or code that is about classifying texts into potentially thousands of categories (topics)? I do have data based on Wikipedia and the number of categories is really ...
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Monotonicity of Jaccard and Dice in multilabel datasets

I understand that Jaccard and Dice follow a monotonic relation on binary datasets because the two are related as $J = {S \over {(2 - S)}}$, and I guess this would be the case when micro-average is ...
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What is the better model architecture and setting when using merge layers?

I am building a deep learning model with dense, dropout, and merge layers. The inputs will be N sentences' feature encoded by BERT (768 dim) and then each will go into the same dense layer as the ...
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43 views

How to implement a LSTM for multilabel classification problem?

I would like to develop an LSTM because I have a variable input matrix. I am zero-padding to a specific length of 800. However, I am not sure of how to classify a certain situation when each input ...
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1answer
41 views

How to interpret Keras predict output?

I am new in Keras and would want to apply a neural network on this dataset: https://www.drivendata.org/competitions/57/nepal-earthquake/ I have proprocessed the dataset transforming categorical ...
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182 views

How to trust the labels generated using ML models?

I have a dataset of patient records. But I do not know whether he is +ve for a cancer or not. So, I do not have the labels in my dataset. Now I can run a machine learning models like clustering to ...
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Classification Model showing different accuracy for SAME data?

This is my first post here, so kindly pardon any commonplace errors. So, i have been training an XGBoost multi-class model on Google Colab. I am using a balanced dataset, with 31000 rows, where each ...
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27 views

Multi-Label Loss function and model training

I'm working on Multi-Label problem i.e output can predict 1 or more label as an output and hence training data also have multiple labels. Somehow I'm not able to map such ML model training. Please ...
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How Hyper-linked library vs traditional library differs from each other as ML problem?

Traditional library can be understood as a system, that archives the collective information from the mediums produced by our society, by indexing them to shelves. It is assumed that libraries have ...
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AUC-ROC for Multi-Label Classification

Hey guys I'm currently reading about AUC-ROC and I have understood the binary case and I think that I understand the multi-classification case. Now I'm a bit confused on how to generalize it to the ...
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Detecting off state in the magnitude of accelerometer data?

I have a univariate time series signal. It's the magnitude of an accelerometer attached to an engine. I need to create an algorithm to detect off state, please see the black lines in the image below....
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76 views

LSTM Multi-class classification for large number of classes

I want to build a model that classifies 473 classes -product categories-, but I'm facing a problem with loss not decreasing. Data I have almost 3,000 data points for each class -473 classes- (data ...
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Recall score for each sample in multilabel classification

Does it make sense to calculate the recall for each sample in a multilabel classification problem? Suppose I have 3 data samples, each having its own true set of labels and predicted set of labels. ...
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2answers
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is there cross validation for xgb classification for multi labels?

is there cross validation for xgb classification for multi labels? I have been search but can not find any cross validation for xgb classifier is using cross validation for xgb or xgb classifier ...
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Transductive Multilabel Classification

I'm trying to use transductive (semi-supervised) multilabel classification on my dataset since I have a low volume of labelled data samples, compared to the unlabelled samples. I found a promising ...
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Initial loss for a multi-label prediction problem

I have seen this: Is there a rule of thumb for the initial value of loss function in a CNN? My question is: how can I know what my initial loss should be in, say, the following situation: 10 ...
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49 views

How to get feature importance from RandomForest using scikit-multilearn library?

I am working on multi-label classification problem, binary case. As a target variable there are five columns with 0-1 values. For a model training I use scikit-multilearn library. Below is my code ...
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369 views

SMOTE for multilabel classification

I have a dataset with 77 different labels. Each sample has one or more of these labels. I did some data analysis and found out that the dataset is highly imbalanced - there are a large number of ...
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3answers
104 views

How to apply supervised machine learning when the target label depends on multiple input rows?

The problem is a multi-label classification problem. Now, I know how to train and classify using single row with several attributes. For example, if the dataset looks like the first table from the ...
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1answer
42 views

Unable to save the TF-IDF vectorizer

I'm workig on multi-label classification problem. I'm facing issue while saving the TF-IDf verctorizer and as well as model using both pickle and joblib packages. Below is the code: ...
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1answer
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Classification algorithm with multiple output for a set of features

I want to build a classification algorithm that will predict multiple values for a set of features. For instance, lets say I have a customer demographic data like Income, age, sex, city and I want to ...
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Generic object detection - unspecified list of classes and high accuracy

As a part of a small project, I would like to create tags for a set of pictures (posters). I know that if I want to recognize a lot of objects I need to have a model that was trained on a large ...
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2answers
215 views

What is the formula to calculate the precision, recall, f-measure with macro, micro, none for multi-label classification in sklearn metrics?

I am working in the problem of multi-label classification tasks. But I would not able to understand the formula for calculating the precision, recall, and f-measure with macro, micro, and none. ...
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1answer
148 views

Multiclassification Error: NotFittedError: This MultiLabelBinarizer instance is not fitted yet

After picking the model, when I try to use it, I am getting error - "NotFittedError: This MultiLabelBinarizer instance is not fitted yet. Call 'fit' with appropriate arguments before using this ...
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1answer
44 views

Making sense of a accuracy plot for a 5 fold training using random forest

I'm using sklearn.model_selection.learning_curve for 5 fold training of data. The code is as given below. ...
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1answer
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152 views

Multi label text classification from thousands of labels

I don't have machine learning experties, but I'm working on a project that has text classification requirements in it. The easiest approach I was able to understand was using fasttext.. It worked, but ...
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1answer
45 views

Decision Tree Classifier to classify values based on values of other columns

I have data with multiple labels, for example My X set is fromt second to third column, and I want to classify either first column or the last column, so I made my Y the last column. The goal is so ...
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1answer
41 views

unique predictions for “multi-label multi-output” classification task

Let’s assume that four participants (A, B, C and D) take on five sport-challenges (e.g. swimming, running, ...). Our goal is to predict the placement of each participant for each challenge. Moreover, ...
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99 views

Multi-label classification based on single-label dataset

I'm looking for a solution to detect different moods/styles expressed by an image. Unfortunately, there is no multi-labeled dataset for this task. The scenario of defining a multi-label ...
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One label dominates in a multiclass classification problem when mapping scores to labels

I am supposed to map each person in my dataset to one of the n categories based on his propensity score. To achieve that, I constructed n models and obtained scores for each category. I did ...
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Can i build an image classification model where each image has multiple labels?

If I am building a model where I need to predict the vehicle, color of it, and make of it, then can I use all the labels for a single image and build my model around it. Like for a single image of a ...
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246 views

Why does classifier chain ask for at least 2 classes, when I have it

I'm using Classifier Chain with logistic regression and when i try to use fit, i get This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1 but I'm ...
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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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32 views

Metrics for multi-class classification. When the prediction is of low quality

I am having a multi-class classification problem, so prediction of an instance to which class belongs to. I am reading that the typical metrics like accuracy or score are very "strict" on such ...
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Classification accuracy based on top 3 most likely classifications

My goal is to recommend jobs to job seekers based on their skill set. Currently I'm using an SVM for this, which is outputting one prediction, e.g. "software engineer at Microsoft". However, consider ...
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How to best use Large images in training set for deep learning

I would like to ask you about how I should deal with the images I have. They are really large. They have this shape: (3000, 4000, 3). I'm working on a multilabel classification model. And I want to ...

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