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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Best Way to combine multiple datasets into one model

I want to make a multilabel image classification model that can detect many different labels. For each label, I can get at least 5000 positive examples and 5000 negative examples. However, my question ...
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Multi-label classification + restriction of predicted classes

Good day. Please help to find a solution. I have built classification for goods to choose the best supplier (tf+keras+lstm) using https://www.tensorflow.org/tutorials/keras/basic_text_classification ...
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how use RBF for primal model of svm?

I know if we want to solve primal model of non-linear SVM, we have to generate new features. for example for kernel (1+xz)^2 for primal problem for any pair of features x1 and x2 we have to generate: ...
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solving svm without using largeagian?

I wrote a SVM model in ampl. (multi classification). I am sure the model is right based on SVM. I didn't use lagragian just solved linear svm . But the result are not make sense to me . most of ...
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can we have different features for different hyperplanes in SVM?

is it possible if we have different features for different classes of svm? For example one of the hyperplane: $$w_1\cdot \text{age}+ w_2 \cdot \text{ trip duration} +w_3 \cdot \text{ income}$$ and ...
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54 views

Transform multi-label problem to multi-class problem

What are the downsides of modelling a multi-label problem as a multi-class problem with a single classifier? Let my clarify what I mean. There at least two ways that one multi-label problem can be ...
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how to reduce the load time of tensorflow text classification model.?

I want to reduce the load time of the model, when testing the model to predict the categories using tensorflow text classification. I am getting the raw data from mongodb collection, which has over 1 ...
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Can we have a sampled sigmoid instead of softmax?

Thh solution proposed here: is for softmax negative sampling. How do we do a sigmoid negative sampling? I couldnt find a corresponding 'tf.nn.sampled_sigmoid_loss' function.
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Does validation loss increase if the dataset is small?

This is my loss vs epoch image... You can see that my model converges too early. However, the frustating point is validation loss does not decrease accordingly compared to training loss. I am doing ...
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1answer
35 views

Is there an algorithm for categorizing unlabeled samples into K classes? [closed]

I am not sure if this would be considered unsupervised, or semi-supervised learning. I am looking for an algorithm that will take N input arrays of features, and then cluster samples(not features) ...
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Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
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Is Elmo equivalent to Fasttext+Bi-directional GRU?

From what I have read, Elmo uses bi-directional LSTM layers to give contextual embeddings for words in a sentence. So if I use a bi-directional LSTM/GRU layer over Fasttext representations of words, ...
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Regarding multi label classification

I am performing multi label classification in python using sklearn. Here is the classification report ...
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Predicting labels which are not independent of one another

I want to make a multilabel classifier where the labels are dependent on one another. Concretely, I have a situation where: If label A is true, then label B is also true. If label B is true, label A ...
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Regarding imbalanced multilabel dataset

I am doing multilabel news classification in python language.The dataset I have has two files. First CSV contains articles at each row. Second CSV contains corresponding labels to each article. Here ...
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1answer
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what is the difference between multilabel and multilabel-multiclass classification?

I am trying to classify news articles into their required category. However I am confused by the above(multilabel and multilabel-multiclass) terminologies. My dataset consists of 2 csv files. The ...
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1answer
35 views

Algorithms inherently supporting multilabel classification

In the documentation of sklearn, it says that several algorithms inherentrly support multilabel classification, such as RandomForest or MLP : https://scikit-learn.org/stable/modules/multiclass.html ...
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How to tackle a multilabel classification problem

I am trying to build a LSTM model for a multiclass classification problem on textual data. Until now, I have only built a model when one input belongs to one of the categories. What do I do when one ...
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29 views

What is the intuition behind using LSTM for classification tasks?

LSTM is good for sequence prediction, because it can remember the previous context. What is the rationale behind using it in classification tasks ? In particular, they have used it for the following ...
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Has anyone implemented multi label classification using hierarchical attention network?

I am going through hierarchical attention network... https://www.semanticscholar.org/paper/Hierarchical-Attention-Networks-for-Document-Yang-Yang/1967ad3ac8a598adc6929e9e6b9682734f789427 I found ...
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1answer
43 views

What's a classifier capable of predicting a variable number of classes

I want to solve what I understand as a classification problem regarding tagging. Let's say an Entity can have 0 or more tags and I want to be able to predict which tags (if any) an entity might get I ...
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Multi-label learning, how to interpret the scores of instances

I am working on a multi-label learning classification problem. When I tune the hyperparameters of the model, the sign of each label (each line on the MLL) remains the same while the scores change. ...
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How to use contrast coding schemes in the case of multiclass target variable? How to encode categorical features if contrast coding fails?

How do you deal with a dataset which only has categorical variables, all of whom have high cardinality? What is the right way to encode high cardinality categorical variables if the target variable ...
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Understanding `get_combination_wise_output_matrix` when investigation a multi-label classification problem

I am currently working on a multi-label classification problem. I am using the scikit-multilearn library (further reading here) I understand that train / test split is important for these types of ...
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1answer
47 views

Best metric in imbalanced classification for multi-label classification

My test data are imbalanced, i tried to use the precision or the gmean as metrics for a multi-label learning model, but both metrics are not very informative. Is there any way to use for example the ...
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1answer
50 views

Splitting train and test in multilabel classification to avoid missing data in the train set

I have a dataset (600 rows) composed of two columns: -Summary: which contains the text of a document -Keywords: which contains the keywords that identify that document. ...
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Why the accuracy is high on both training and validation set but very low on test set?

I'm using Tensorflow to train a classifier for image recognition, the model below is built via Keras. The original data is (50000, 3072), and reduced to (50000, 100) with PCA. The explained ratio is ...
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55 views

how to get labels in face recognition in keras

I was building a face recognition system the model is complelete but i am having minor issues while predicting them. I used the Image data generator to load images from by train and test folders ...
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How to calculate the ranking loss in multilabel classification?

I can calculate the ranking loss using sklearn. But I am not able to understand this calculation manually in a step by step process. Can anyone explain? ...
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1answer
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Using Keras how and what do I need to export to use my classifier independently?

I have a basic question that I can't seem to find an answer to. I built and trained with good results (above 90% accuracy) a NLP Log classifier that takes in a UTF-8 payload and classifies it into 32 ...
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167 views

What's the difference between multi label classification and fuzzy classification?

Is it just the between academics and practitioners in term usage? Or is theoretical difference of how we consider each sample: as belonging to multiple classes at once or to one fuzzy class? Or ...
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64 views

DecisionTreeClassifier for multi label classification giving outputs as single classes

I have built a DecisionTreeClassifier for multi-label classification with details given on https://scikit-learn.org/stable/modules/multiclass.html with input data in shape ...
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39 views

Can an output class be defaulted?

In my use-case of multi-class classification, my data distribution is like below: It might be too silly to ask this (and possibly could be gravely wrong), but is there a provision to default an o/p ...
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184 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-class classification as a hypothesis testing problem

I'm diving into the logistic distribution and its applications in classification problem (see my old question for more details about my idea). As discussed in my old post, logistic regression, in ...
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1answer
46 views

Multilabel classifcation in sklearn with soft (fuzzy) labels

I have a model which is trained in sklearn on a 5-way classification problem, which performs relatively well (there are kNN and SVM versions, and both reproduce a test set with high accuracy). When ...
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1answer
169 views

Balancing XGboost still skews towards the majority class

I have unbalanced dataset for multiclass classification and I tried to use the class weights option in XGboost and the classifier still tends to favor the majority class. I am not sure if I need to ...
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1answer
41 views

What are some possible reasons that your multiclass classifier is classifying alll the classes in a single class?

I have unbalanced classes. Group1 N = 140 Group2 N = 35 Group3 N = 30 I ran the code on this data and all the Groups got classified as Group1. I thought that since group1 is the majority group this ...
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1answer
69 views

How to utilize user feedback due to miss-classification when correct class label is unknown?

Suppose we are developing an app which is supposed to predict a dog's breed by it's picture. We trained a classifier (in my case an MLP) using some dataset and shipped the app to users. Now suppose ...
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2answers
244 views

How mean and deviation come out with MNIST dataset?

I am a novice at the data science, and I notice some repository state the mean value and deviation in MNIST dataset are ...
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1answer
270 views

Confusion matrix in multilabel classification of an object in more than one class simultaneously

Regarding a classification problem where for example given an image which depicts a human and we are trying to predict their stance and their behavior. For example Human 1: 'Sitting' and 'Eating' in ...
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34 views

Transform a multiclass dataset into a multi-label one

I have a dataset of feature/label pairs. My labels are probabilities of each feature vector to belong to the K classes. Here is an example for K = 3: ...
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429 views

LSTM sequence prediction: 3d input to 2d output

I have this LSTM model ...
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28 views

LSTM RNN application [closed]

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), previous grades (Pass, ...
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1answer
20 views

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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59 views

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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195 views

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
705 views

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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532 views

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 ...