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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Classifying multilabel images with TensorFlow

The dataset that I am categorizing with TensorFlow ML library contains multiple labels per image. The contents are real estate images photographed from outside that are analyzed for various image ...
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Testing a tensorflow network: in_top_k() replacement for multilabel classification

I've created a neural network in tensorflow. This network is multilabel. Ergo: it tries to predict multiple output labels for one input set, in this case three. Currently I use this code to test how ...
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Multilabel Classification - increasing the confidence

I have a basic multilabel topic classifier(Tfidf vectorizer with OneVsRest Classifier) built on some customer reviews. I observed that there are some classes with right features but it still predicts ...
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What is the difference between multilabel dataset and special dataset with respect to imbalance problem in datasets?

i have a multilabel data set which is imbalenced and noisy.i used BR approach to convert single lablel and perform balanceing.data is fragmented into one class now i want to merge these fragmented ...
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1answer
326 views

CNN tagging such that each input could have multiple tags

Thanks in advance for reading my question! I've been using CNNs to classify text using Keras and TF. My data is strings "I read the news" or "I read machine learning news" and my ...
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0answers
277 views

Using tensorflow to test a variable amount of correct labels

I'm using a neural network to analyze item choices made by players in a computer game. In the game players can choose between 0 and 7 items. Right now I'm struggling with how I can evaluate my data. ...
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GPU Utilisation Issues

I observed that my GPU's memory is being consumed but the Utilisation stays 0. Because of this, my model is taking forever to load. I have tweaked this code to handle multilabel data. The only changes ...
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1answer
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Activation method and Loss function for multilabel multiclass classification

I am using CNN for Sentence Classification code by Yoonkim. This is used for text classification. I noticed that he uses softmax layer and negative log likelihood error. This is optimal for single ...
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2answers
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How to deal with classification problem where labels are non uniformly distributed?

I have a data set which has around 1000 samples and are divided in 4 groups - A, B ,C , D. The problem I am facing is that there are very high number of data sample which have B and C s output. They ...
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Score for concordance of two classifications with different number of classes

I am searching for a score to compare two different classifications of the same observations. I was thinking about Adjusted Rand Index or Adjusted Mutual Information, but the problem is that the ...
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3answers
506 views

Training multi-label classifier with low quality training set

So I'm creating a topics classifier where a document may be tagged for several different topics, let's say - A, B while actually the document belongs to A, B and C. In the training stage I want the ...
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3answers
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Multi-label Text Classification

I am trying to build a multi-label classifier for suggesting tags on blog posts. The textual data is full of noise. The approach I have been following until now was a BOW approach with Tf-idf ...
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3answers
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Categorizing Customer Emails

I am working on a project for a company which needs to categorize customer e-mails regarding loans and insurance. The e-mails are labeled uniquely from set of 13 category labels. The number of records ...
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3answers
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What is a subspace and what is a shared subspace?

I'm totally new in machine learning. The first confusing concept is subspace. In multi label classification we have to share the subspace. What does one mean by that shared sub spaces?
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1answer
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Solving multi label image classification using TimeDistributed dense layer

I have a multi label image dataset having 5 labels. Each image can have more than one label at the same time. I am using a convolutional neural network to extract features and those extracted features ...
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0answers
457 views

RTextTools multi-label classification

In follow up to my previous question, I was able to label survey responses based on 70 categories using RTextTools. Each survey gets one label while if manually coded some would have up to 8 labels. ...
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2answers
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Deep Learning with Spectrograms for sound recognition

I was looking into the possibility to classify sound (for example sounds of animals) using spectrograms. The idea is to use a deep convolutional neural networks to recognize segments in the ...
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0answers
174 views

Data categorization

I'm using Google API to categorize and predict problems with laptops (Hardware, Software, Network, Customer satisfaction, No reason). I inserted my training data and categories are very well evaluated ...
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7answers
14k views

Python library that can compute the confusion matrix for multi-label classification

I'm looking for a Python library that can compute the confusion matrix for multi-label classification. FYI: scikit-learn doesn't support multi-label for confusion matrix) What is the difference ...
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2answers
202 views

Impact of unlabelled documents for label prediction via SVM

I have a corpus of text documents, some of which are labelled by analysts with label L. I am using this data to train an SVM for predicting if a new document should have label L. So far it's straight-...
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1answer
78 views

how to make new class from the test data

I have a list of accounts as data set and I need to group the accounts that refer to the same user using many features. I'm thinking to use machine learning( but I'm new in this domain), because I ...
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1answer
273 views

Spark 1.5.1: Train many binary classifiers, save them, then use them on new data

I have a DataFrame representing an annotated dataset with 300 labels. The DataFrame looks like follow (the first row is just to explain the columns): ...
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1answer
749 views

SPARK 1.5.1: Convert multi-labeled data into binary vector

I am using SPARK 1.5.1, and I have DataFrame that looks like follow: ...
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1answer
504 views

One multilabel classifier or one for each type of label?

Let's say I need to classify addresses with scikit-learn, so if I want my classifier to be able to classify addresses by the street name, and post/zip code, should I do a OneVsRest classifier, or ...
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1answer
451 views

Python library to compute some metrics for multioutput-multiclass classification task

Is there any Python library that provides ready-to-use metrics to analyze the performance of a classifier for a multioutput-multiclass classification task? scikit-learn doesn't have this option yet (...

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