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Questions tagged [multilabel-classification]

Multi-label classification refers to the problem in Machine Learning of assigning multiple target labels to each sample, where the labels represent a property of the sample point and need not be mutually exclusive.

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Tensorflow - Multilabel classification loss decreasing slowly/not changing at all

I am working on a neural network in Tensorflow. My network performs multilabel classification to predict which users bid on which cars. I have a CSV with three columns; User IDs, Highest bid, and Make names (car models), however I only use User IDs…
SquishyAura
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How calculate prediction accuracy of OneVsRestClassifier?

how I can calculate the prediction Accuracy and F1 Score of OneVsRestClassifier? >>> from sklearn import datasets >>> from sklearn.multiclass import OneVsRestClassifier >>> from sklearn.svm import LinearSVC >>> iris = datasets.load_iris() >>> X, y =…
RJFF
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How multi label classification works in scikit-learn decision tree?

I had a problem to classify inputs which have more than one label. So problem is multi-label classification. I used scikit-learn Decision Tree classifiers to do this and it gives pretty good results at initial stages. But, I am wondering how is it…
Urvish
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NLP multi-class classifier loss can’t go down

I'm building a classifier for a QA bot, and have a dataset for 8k questions, and 149 different Answers. I got some problems when training my model; the "loss" won't go down as I expected so I am asking for your help... Here is my method: I use…
p208p2002
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LSTM with multiple time-series

I am training LSTM for multiple time-series in an array which has a structure: 450x801. There are 450 time series with each of 801 timesteps / time series. The labels are classes with assigned integer from 1 to 6, so the dimension of the label is…
user2754279
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Sklearn Multilabel ML: ValueError: Multioutput target data is not supported with label binarization

I am building a program that assigns multiple labels/tags to textual descriptions. I am using the OneVsRestClassifier to label my textual descriptions. xTrain, xTest, and yTrain are all 'numpy.ndarray'. This does seem strange considering that I have…
Henry Zhu
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why R can handle big data set but optimization solver can not?

I wrote SVM in AMPL , data has 9236 rows . In AMpl it can not be solved . After 30 minutes I get error that memory is not enough. but for that data set I use R and it takes 60 second to solve! it is very weird, isn't it? I am wondering how R solve…
sherek_66
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Two target labels and custom loss function in python

Using python and any machine learning library, I'm trying to have two target labels and a custom loss function. From my understanding, there is only one way to achieve this and that is by using Keras. Is this correct? Here is a list of other things…
Rkey
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How to improve accuracy when outputs not equiprobable?

I have a classifier of images that each have exactly one of 5 labels [0-4]. I have hit an accuracy wall at ~72% and am looking for a way over it. I have noticed that my classes [in my training set] are quite 'heavy' in 0's, and a little less 'heavy'…
Wascally Wabbit
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In SQL how do I group by every one of a long list of columns and get counts, assembled all into one table?

I have performed a stratified sample on a multi-label dataset before training a classifier and want to check how balanced it is now. The columns in the dataset…
rjurney
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How to perform Multilabel classification using spark ml in Java

I have built a model that classifies emails based on keywords in subjects(features) into 10 different work_categories (labels). However, this task might consist of possibility where the emails should be categorized in more than a single label. For…
Naseeb Thapaliya
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Balance problem for classification on Cleveland Dataset

I’ve questioned the way famous Cleveland heart disease dataset labels its objects here This dataset is very unbalanced (many objects of “no disease” class). I noticed that many papers that used this dataset used to combine all the other classes and…
heresthebuzz
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XGBoost with Multilabel

I am trying to use this appoach https://stackoverflow.com/a/44117716/11102206 to predict 24 variables, but I'm getting ValueError: Multioutput target data is not supported with label binarization. Any help X_train, X_val, y_train, y_val =…
user11102206
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Preprocessing data in Multi-label classification Python

My dataset structure: Text: 'Good service, nice view, location' Tag: '{SERVICE#GENERAL, positive}, {HOTEL#GENERAL, positive}, {LOCATI ON#GENERAL, positive}' And the point here is that I don't know how can I structure my data frame. If you have any…
Lắc Lê
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How can i make the run time of Multi-Class Classification faster?

I'm trying to train and run Multi-Class classifiers for Random Forest and Logistic Regression. As of now on my machine which has an 8GB RAM and an i5 core, it's taking quite some time to run inspite of the datasize being hardly 34K records. Is there…
Harshwardhan Nandedkar
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