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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15 views

how can I replicate working of Multi Label Binarizer from sklearn package in R?

I want to achieve same working of MultiLabelBinarizer from sklearn.preprocessing package in R. I have list of labels for each example (for Predicated and Actual) like below. ...
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13 views

Neural Network to classify target subitens?

Nowadays i am doing a research project where i am allowed to classify given a sample from a large dataset with an already existed sample/target model the belonging target, but in my project there are ...
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45 views

Risk score from Neural Network classifier (more than 2 categories)

I am trying to use a Neural Network to perform multiclass classification. The classes represent Insurance Risk Level. The most risky level is Level 1, the least risk corresponds to Level 10. The ...
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11 views

Scaling ML/DL classifier

I have been trying to find some guideline through google/stackoverflow for scaling a classification system. E.g. how can I scale a face recognition system if we want to add new people into the system? ...
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21 views

Multilabel image classification failure with a specific dataset

I'm having an issue with a specific dataset. My training for multilabel image classification is returning [class1 and or class2 and or class 3] (only 3 classes for every image) when there are 13 ...
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33 views

Weighing each label in multi-label classification

If, in addition to predicting labels using a multi-label classifier, I'm interested in predicting the weight of each label, what approach should be taken? To give an example, let's say I'm trying to ...
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20 views

Issue with multilabel image classification only returning a couple (incorrect) classes

I followed this tutorial: https://medium.com/@vijayabhaskar96/multi-label-image-classification-tutorial-with-keras-imagedatagenerator-cd541f8eaf24 and wrote some of my code for multilabel ...
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7 views

Cross_validation is decreasing accuracy?

I have certain dataset to train a model. The dataset is not very small in size. First, I split the dataset into training and validation data using traintestsplit (80-20), train the model on training ...
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24 views

Split tuples with labeled samples in training, validation and test sets

I was reading through all the internet and i can't find nothing similar what i am looking for, i only saw this topic for pd.DataFrame, np.ndarray and list datasets but i didn't find nothing explaining ...
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Classify the input set into categories based on pre-defined rule set

I'm trying to solve a problem where there are 2 input files given, Input 1: A set of strings in the format. All the strings start with "A". A-B-C-D A-B-C-3 A-X-Y-Z-4 A-X-5 A-X-P-Q-R A-X-P-Q-S A-M-9-...
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Improving classifcation when some are less represented?

I have a multi-class classification problem. It performs quite well but on the least represented classes it doesn't. Indeed, here is the distribution : And here are the classification results (I took ...
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Big dataset for multi-class classification can't be dasked and split, normal one can't be handled

I have a huge dataframe (550MB), the lending club one available here, and I have to predict the class of the grades. The dask dataframe is : ...
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27 views

What (probabilistic models) can only output decisions when they are certain?

I'm basically looking for approaches, models, algorithms for the following situation (a fault diagnosis problem): I have an input set $\{x_i\}_{i \in \{1..m\}}$ with $n$ binary features of cases (...
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21 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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39 views

Using a LinearSVC() for multilabel classification with MultiOutputClassifier() in a pipeline in sci-kit learn

My input data is a (23948,) pandas.Series of strings containing newspaper headlines. My target are 20 labels of the headline (e.g. 'crime', 'politics') each binarily encoded with [0, 1]. The labels ...
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Multilabel Image classification via multiple binary datasets

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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27 views

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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22 views

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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14 views

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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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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21 views

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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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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42 views

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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23 views

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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36 views

Regarding multi label classification

I am performing multi label classification in python using sklearn. Here is the classification report ...
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18 views

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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81 views

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
55 views

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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60 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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51 views

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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30 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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18 views

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
46 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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20 views

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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19 views

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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32 views

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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68 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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62 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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29 views

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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78 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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25 views

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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22 views

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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202 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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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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249 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 ...