Newest 'multilabel' Questions

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Initial loss for a multi-label prediction problem

I have seen this: https://datascience.stackexchange.com/questions/18991/is-there-a-rule-of-thumb-for-the-initial-value-of-loss-function-in-a-cnn Since my question is more mathematical in nature, I ...

loss-functions multilabel

asked Feb 11 at 20:52

StatsSorceress

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25 views

SMOTE for multi-label 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 ...

asked Feb 4 at 9:25

Aishwarya A R

1011 bronze badge

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13 views

Multilabel classification and regression on time-series data

I am trying to develop an LSTM network on a vehicle dataset I have obtained from my professor. The dataset in about vehicle driving in a roundabout. I have the following tasks to complete 1. Classify ...

time-series multivariate-analysis lstm multilabel

asked Jan 22 at 7:22

Sharan Magavi

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19 views

How to maximize subset accuracy for multilabel multiclass image classification

I working on multi-label multi-class image classification. I am using TensorFlow. Currently I am using sigmoid on output layer with binary_crossentrpy. Model is ...

neural-networks classification tensorflow multi-class multilabel

asked Jan 17 at 9:12

Vivek Mehta

1012 bronze badges

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0answers

38 views

How to choose operation point from precision recall curves for multi-label classification

Is there a commonly accepted method for selecting an operating point for a multilabel classifier to optimize for each of these aggregate metrics: micro averaged recall at some minimal acceptable ...

machine-learning classification precision-recall decision-theory multilabel

asked Jan 1 at 19:06

Ryan Lambert

213 bronze badges

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91 views

Multi label classification baseline model

I have a multi label image classification task with a large number of labels (7000) . I am using ImageDataGenerator to flow the dataset from a file. Before I start ...

classification conv-neural-network image-processing multilabel

asked Dec 30 '19 at 15:37

ok i quit

1

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0answers

18 views

How to handle a big5 personality traits task

I have a dataset consists of N tweets annotated with the big 5 personality traits (extroverted, stable, ...

regression classification psychology multilabel

asked Dec 26 '19 at 16:39

Ghanem

1355 bronze badges

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0answers

8 views

Neural network embedding layers allowing multiple class-membership features

Is there a version of embedding layers for neural networks that allows for multiple class-membership features? Any frameworks that have implemented this? E.g. imagine we are trying to predict ...

neural-networks multilabel embeddings

asked Dec 1 '19 at 21:17

Björn

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10 views

Good way to solve product recommendation

I need to recommend products based on top selling products for a given day in the past. The only independent variable is date which i can derive some information from such as weekday, month etc. The ...

recommender-system multilabel

asked Nov 20 '19 at 7:37

Rob

112 bronze badges

2

votes

1answer

121 views

F1-Score in a multilabel classification paper: is macro, weighted or micro F1-used?

I read this paper on a multilabel classification task. The authors evaluate their models on F1-Score but the do not mention if this is the macro, micro or weighted F1-Score. They only mention: We ...

classification scikit-learn multilabel f1

asked Nov 16 '19 at 18:58

chefhose

1215 bronze badges

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94 views

Interpreting hamming loss for multilabel classification

I have a multi label - multi class classifier that aims to predict the top 3 selling products out of 11 possible for a given day. Using scikit learn's OneVSRest with XgBoost as an estimator, the ...

python model-evaluation accuracy xgboost multilabel

asked Nov 14 '19 at 19:13

Rob

112 bronze badges

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46 views

Why is softmax considered counter-intuitive for multi-label classification?

In the FB paper on Instagram multi-label classification (Exploring the Limits of Weakly Supervised Pretraining), the authors characterize as "counter-intuitive" their finding that softmax + ...

classification cross-entropy softmax multilabel

asked Oct 30 '19 at 20:07

max

1,10311 silver badges22 bronze badges

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153 views

When does multi-task learning make more sense than multi-label classification?

As part of writing a book on machine learning, I am creating an extreme multi-label stack overflow question tagger for thousands of tags with varying numbers of training examples and I’ve approached ...

classification neural-networks natural-language multilabel multitask-learning

asked Oct 26 '19 at 22:25

rjurney

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0answers

102 views

How to you label (caption) the table title? (for example:Tests of Between-Subjects Effects for One-way ANOVA)

How do you lable/caption a table under One-way ANOVA? Tests of Between-Subjects Effects for One-way ANOVA OR ...

anova multilabel labeling

asked Oct 24 '19 at 18:49

aan

814 bronze badges

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votes

1answer

38 views

Is skip-gram model of word embedding actually a multi-class task not a multi-label task, right?

So curious about this question, that I can't describe it in short. Please forgive me. Description： From multiclass and multilabel algorithms, we can get the definition of the multi-class and multi-...

machine-learning tensorflow multi-class word-embeddings multilabel

asked Oct 10 '19 at 7:43

Alexander

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2answers

794 views

What type of multi-label method does sklearn's random forest classifier use? [closed]

I have trained RandomForestClassifier on data with 3 labels. The label set Y looks like this: ...

python random-forest scikit-learn multilabel

asked Sep 9 '19 at 15:54

Bill Robinson

333 bronze badges

0

votes

1answer

130 views

Oversampling a multi-labeled data set

Given a data set where each individual data point can be assigned to more than 1 class (a multi-class, multi-label data set), are there any guidelines for calculating oversampling weights, i.e., the ...

classification multi-class multilabel oversampling

asked Aug 23 '19 at 14:33

tsorn

1478 bronze badges

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votes

1answer

68 views

multiple measurements for classification; which one to choose?

There are five different classes (labels) where the new points have to be classified at. For each new point, five different measurements are conducted, resulting into similar although different values ...

classification repeated-measures similarities multi-class multilabel

asked Jul 23 '19 at 12:59

Alex

193 bronze badges

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votes

2answers

116 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, ...

neural-networks lstm word-embeddings multilabel gru

asked Jun 25 '19 at 5:57

Atif Hassan

1684 bronze badges

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0answers

86 views

influence of oversampling on Semi-supervised multi-label learning

I have suggested a semi-supervised approach for the hierarchical multi-label classification task. I have included the MLSMOTE oversampling technique as a pre-processing step, and then evaluate the ...

multilabel semi-supervised oversampling

asked May 21 '19 at 6:42

Abir Masmoudi

113 bronze badges

0

votes

0answers

80 views

Label Switching and Pivot method

I am working on the so called label switching problem in Bayesian inference with Gaussian Mixture Models. To put in a nutshell, when your favourite MCMC samplers estimates the parameters of your GMM,...

machine-learning bayesian mcmc algorithms multilabel

asked May 11 '19 at 22:32

MarcM

734 bronze badges

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10 views

What is the best method using supervised learning to label images with single-pixel-level defining features?

The images are in later form of size 170 where each index could be a -1, 0, or 1. The images are multi-labeled, with 8 possible labels. The issue is that there are often only slight differences ...

supervised-learning multilabel

asked May 1 '19 at 0:33

Benjamin Spiegel

12 bronze badges

1

vote

1answer

127 views

Optimising recall for multi-label classification?

I'm working on a multi-class multi-label classification problem where text (let's say comments on a website) should be assigned (possibly multiple) labels. There is a neutral (negative) class and ...

machine-learning precision-recall multilabel

asked Apr 15 '19 at 5:21

Milad Shahidi

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20 views

Are these Multi-label document classification experiment steps sensible?

I plan to filter an input document using 4 different labels. Just for an example, a document discussing about movie summary needs to be labeled with 4 labels (Romance, Drama, Fiction, Hollywood). ...

machine-learning classification natural-language multi-class multilabel

asked Apr 14 '19 at 12:49

adjective_noun

237 bronze badges

1

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0answers

860 views

How to deal with an imbalanced dataset for multi-label classification?

You can consider me novice to intermediate at best with Machine Learning. For the past few months, I've been developing a neural network that learns to play a 3D fighting game by trying to mimic how ...

machine-learning classification neural-networks unbalanced-classes multilabel

asked Apr 9 '19 at 22:25

Polyrogue

113 bronze badges

1

vote

2answers

104 views

how to build multiple independent binary logistic regression classifiers?

I have to build a logistic regression classifier to predict $\mathbf{y}$ given $\mathbf{x}$ where $\mathbf{x} \in \Re^{n}$ is an image and $\mathbf{y} \in \Re^{m}$ is a binary attribute vector (of $m$ ...

machine-learning logistic scikit-learn keras multilabel

asked Mar 15 '19 at 12:33

Upendra Pratap Singh

1,1961 gold badge14 silver badges21 bronze badges

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26 views

How to call label encoding in multi-label case?

In the multi-label classification, one way to encode the data is to make a table with 1 row for each entry and one column for each label. For each entry/label pair, you get a 0 if the entry has the ...

terminology categorical-encoding multilabel

asked Mar 6 '19 at 13:34

Statistic Dean

1013 bronze badges

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20 views

Machine Learning, which kind of classification should i use?

So im trying to make a ML classifier model to my data. My data has many X(variables [texts, integers, binaries etc.]) and 5 output(Y) information. In short, lets say i have 5 different places to put ...

machine-learning classification python multi-class multilabel

asked Mar 4 '19 at 8:07

Oguz

12 bronze badges

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42 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: D1 = { (V0, [0.33,0.33,0.33]), (V1, [0.9,0.07,0....

classification multinomial multilabel

asked Feb 24 '19 at 7:57

user3091275

1935 bronze badges

3

votes

1answer

538 views

Multi-label classification with neural networks: Are correlations between class labels taken into account?

I am solving multi-label classification problem (assigning each image 1 to N labels) and want to use neural network (like in this post). Does this approach take correlations between class labels into ...

classification correlation neural-networks multilabel

asked Feb 12 '19 at 19:35

Miroslav Sabo

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votes

1answer

419 views

Learn threshold for multi-label classification

I have a multi-label problem which I'm tackling with a NN. To get the multi-label scores, I use a tanh on the last layers (as suggested in the literature), and then selecting the ones corresponding to ...

neural-networks threshold multilabel

asked Jan 24 '19 at 12:10

McKracken

312 bronze badges

1

vote

0answers

31 views

Weakly supervised learning and missing labels for data that likely contains that label

I would like to know how to deal with data that misses a label, but is likely to contain the label in a weakly supervised setting. Weakly supervised background Since labeling is a time consuming and ...

machine-learning multilabel semi-supervised

asked Dec 27 '18 at 3:19

NumesSanguis

1314 bronze badges

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vote

0answers

460 views

How to use data_utils.WeightedRandomSampler and still be able shuffle training data in Pytorch?

I am working on the multi-label classification task in Pytorch and I have imbalanced data in my model, therefore I use data_utils.WeightedRandomSampler method ...

classification sampling weights multilabel

asked Dec 18 '18 at 10:28

ViniLL

112 bronze badges

1

vote

0answers

118 views

How to evaluate the results of a multilabel classifier using the predicted probabilities?

I can use sklearn accuracy_score to evaluate de predicted values of my multilabel classifier. But how can I evaluate the predicted probabilities obtained with predict_proba?

classification python scikit-learn model-evaluation multilabel

asked Nov 16 '18 at 16:24

Hohenheimsenberg

1435 bronze badges

1

vote

1answer

224 views

Activation function when there are several output labels

If we had a NN to, let's say, clasify images of digits, but each image could contain more than 1 digit (all different), is there any problem in using a 10-dimensional output layer (representing digits ...

classification neural-networks multilabel

asked Nov 14 '18 at 20:51

Cándido Otero

154 bronze badges

2

votes

1answer

592 views

How to manually balance unbalanced multi-class/multi-label data?

I have a multi-class and multi-label classification problem, i.e.: each sample can have more than one label associated to it and there is a total number of M ...

classification unbalanced-classes multi-class multilabel

asked Oct 7 '18 at 11:08

fsamu

1064 bronze badges

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votes

1answer

26 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 ...

classification cart unbalanced-classes multilabel labeling

asked Oct 3 '18 at 9:56

Minila S

511 silver badge6 bronze badges

3

votes

1answer

378 views

Choosing the number of labels in a multiclass classification problem

I've recently come accross a multilabel classification problem. Here, multiple labels can be simultaneously assigned to a single instance. I am interesting how one determines the number of labels to ...

machine-learning classification multilabel

asked Sep 1 '18 at 10:29

sdgaw erzswer

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1

vote

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86 views

How to create an imbalanced dataset without leading to classifier overfitting

I am working on semi-supervised multi-label classification method that intrinscly deal with the imbalance problem, commonly present in multi-label datasets. That's why, i want to create an imbalanced ...

unbalanced-classes multilabel

asked Aug 25 '18 at 11:06

Abir-Researcher

112 bronze badges

1

vote

0answers

132 views

PR curve and confusion matrix members for multiclass and multilabel classification problems [closed]

I am looking for any libraries which provide out of box support for calculating PR curve and the confusion matrix items(not just count but the items which contributed to the count as well) for ...

machine-learning multi-class multilabel spark-mllib

asked Aug 23 '18 at 23:26

sachi1325

112 bronze badges

1

vote

1answer

226 views

how to limit one label while doing multi-label classification

I have a data set with 7 labels. I would like to apply multi-label classification on that. by that, each instance may have more than one label associated. now let's explain what I want. Rules in my ...

classification scikit-learn multilabel

asked Aug 12 '18 at 4:58

sariii

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1

vote

0answers

48 views

Accuracy in multi-label classification [duplicate]

In a multi-label classification, the accuracy is commonly defined as [1] $$ \text{Accuracy}(\boldsymbol{Y},\, \boldsymbol{Z}) := \frac{1}{n} \sum_{i=1}^n \frac{\lvert Y_i \cap Z_i \rvert}{\lvert Y_i \...

accuracy model-evaluation multilabel

asked Jul 18 '18 at 11:09

ma0ho

1111 bronze badge

3

votes

0answers

340 views

Measure agreement among experts in multi-label classification task

I was wondering whether there is a metric that can be used in order to compute the agreement, and therefore something like an upper bound for classifiers, among expert-labelled data. Assume there is ...

classification metric multilabel

asked Jun 26 '18 at 13:36

displayname

2472 silver badges12 bronze badges

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votes

1answer

647 views

multi label misclassification rates

I'm looking for a way to efficiently describe the performance of a multi-label classification model (if possible, something like confusion matrix for the multi-class classification). I'm not sure if ...

multi-class confusion-matrix multilabel

asked Jun 11 '18 at 19:54

Maystro

1012 bronze badges

1

vote

0answers

369 views

Multi-label classification, binary loss concerns

I am solving a multi-label audio classification task with neural networks. The dataset is comprised of 10 classes, and the input data to the network are audio files where two of these classes are ...

classification neural-networks loss-functions multilabel cross-entropy

asked May 22 '18 at 9:07

sdiabr

5973 silver badges16 bronze badges

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votes

1answer

76 views

Neural Networks: How to do class prediction from murky labels

I'm conducting an experiment with the MNIST digit data - handwritten digits 0-9, each example composed of 28x28 bitmap of pixels. Imagine a collection of examples is drawn at random without class ...

classification neural-networks conv-neural-network multi-class multilabel

asked May 21 '18 at 20:51

Patrick McCarthy

4354 silver badges10 bronze badges

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0answers

122 views

Multi-label classification with Neural networks

Task: Multi-label classification of sounds using neural networks. (Urbansound8K Dataset) Problem: How to best generate my combined dataset, considering maximum 2 sounds combined at the same time. ...

classification neural-networks python multilabel

asked May 17 '18 at 12:49

sdiabr

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1

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0answers

130 views

Multi-label classification: overlapping or graph structure among labels

I am doing multi-label text classification. I have 5000 classes and there is a graph structure among these classes. How to deal with multi-label classification where there is overlapping or graph ...

classification text-mining multilabel

asked May 8 '18 at 15:36

clement116

236 bronze badges

1

vote

1answer

275 views

Best apparoaches for feature selection in multilabel classification

I have dataset which consists of around 46k observations and 20k features. The target vector is of length 75 (and so the target matrix is 46k x 75). among the features few are categorical and others ...

machine-learning classification multilabel

asked Apr 27 '18 at 8:50

prashanth

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vote

1answer

712 views

Multilabel classifier Prediction using categorical cross entropy loss model

I am doing a multilabel classification using categorical cross entropy as the loss function. My input labels are a 1d vector of the form = [2 4 5..] First I convert my labels to categorical using, ...

classification prediction multilabel

asked Apr 9 '18 at 3:44

Danushka Bandara

233 bronze badges

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