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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17 views

Changing order of LabelEncoder() result

Assume I have a multi-class classification task. The labels are: Class 1 Class 2 Class 3 After LabelEncoder(), the labels are transformed into 0-1-2. My questions are: Do the labels have to start ...
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Feature vector representation

I have a clarification. I have to create a classification model for certain set of documents. We are supposed to flag it anamoly or not based on certain terms in the document. My question is the terms ...
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How to read the predicted label of a Neural Netowork with Cross Entropy Loss? Pytorch

I am using a neural network to predict the quality of the Red Wine dataset, available on UCI machine Learning, using Pytorch, and Cross Entropy Loss as loss function. This is my code: ...
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Best Way to tackle to time series classification problem?

I have a dataset where the input is a dataset for ICU patients where each ICU stay has 40 features (20 vitals, 20 lab values) and multiple time steps (the stays' length is between 6 and 19-time steps)....
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How to train BERT (multi label) on imbalanced dataset for search query category classification

I have a dataset of 2 million search queries relative to 7000 categories. same query could have multiple categories. Aim is to predict category/categories for query with confidence score. I tried ...
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30 views

How best to convert label classification into regression?

I have a dataset of genes for which I'm trying to predict genes that cause a disease. Originally I was doing this with a multilabel classification. I had 3 groups: I labeled already known disease-...
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1answer
30 views

Multi-label text classification. 3-4 labels per text, 100 labels overall

My first pet ML project, so please pardon if I phrase something incorrectly. Recently I had IMDB sentiment analysis binary classification practice on Tensorflow site. Now I am keen to do multiple ...
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34 views

Best algorithm/model to establish relevance between events utilizing mixed data type (Tags, Time, x_coordinate, y_coordinate)?

I'm building a relevance ranking system for incidents occurrence and prevention. My goal is to use four attributes to establish relevance: tag (About 500 tags), x_coordinate, y_coordinate and time. ...
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1answer
25 views

Test set larger than train set [closed]

There is a two class dataset with 1121 values in total, having 230 from same class and 891 from the other class. The training set is choosen as 230+230=460 from both classes and the test set as the ...
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Suggestions for Open-Source Tool for Image Classifications (with Nesting)

I'm looking for an open source tool to assist my colleagues and I to label images for a machine learning application. We don't actually need bounding boxes or anything to pinpoint regions within each ...
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How to calculate separate binary accuracy metric for each label in a multi-label classification in Keras?

I'm stuck with this: def multilabel_binary_acc(y_true, y_pred): return [K.equal(y_true[:,n], K.round(y_pred[:,n])) for n in range(y_pred.shape[1])] But it ...
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43 views

Steps to perform multi label word classification

I am trying to classify small strings into three categories. Examples: ...
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1answer
37 views

How to apply MultiOutputClassifier to a dataset for Naive-Bayes algorithm

I have a dataset which is as follows, (it's taken from an article online and I have been trying to Naive Bayesian algorithm on it) Original Dataset y attribute After having done some manipulations (...
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1answer
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How to cluster label (in a multilabel classification problem) which mostly appear together in a class

To cluster label (in a multilabel classification problem) which mostly appear together in a dataframe? For example, I have this dataframe: ...
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1answer
56 views

Multi-label classification with nested features

I need to perform a multi-label classification. I have three features and they are nested. I am unsure how to combine this or what kind of classification algorithm would be best. Some multi level ...
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What kind of learning problem is this?

Say I have $n$ multi-class classification problems $p_1$, ..., $p_n$. Each of these have their own training data. While they are all distinct problems, there may be similarities in their data (which ...
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1answer
51 views

Softmax regression cost function code [closed]

I really do not understand what does this code do M = sparse.coo_matrix(([1]*n, (Y, range(n))), shape=(k,n)).toarray() The code is related to calculating the ...
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1answer
27 views

2-label dataset for 3-label classifier?

I have a dataset containing headlines and sentiment related to those headlines. The headlines have been filtered out from another bigger dataset using the following criteria: keep the ones that have a ...
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1answer
28 views

Which is better: multi-output model or separate models for similar tasks?

I am working on two problems: classification of images into high-level classes (e.g. shoe, dress, jacket etc.) classification of the attributes of the same images on a lower level (e.g. shoe style, ...
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1answer
29 views

How to find the feature regions where each label is the most expected when using decision trees?

Given a decision tree for classification for example this one: What is the way to find the feature domain (petal and sepal width and length) where a sample would most likely occur in the feature ...
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1answer
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ML - Labelling - number of possibilities [closed]

I've started learning ML and stuck with the number of possibilities in labelling. I have a sample which comprises 4 attributes (binary) (from the book Apprentissage artificiel, Antoine Cornéujols) ...
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1answer
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Which model for a content suggestion in which only some of the items are currently available

I am trying to understand the type of model that would be used in a content suggestion scenario where not all of the choices are available at a given time. For example, when an online movie ...
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205 views

ValueError: bad input shape

I have multilabel problem. I was using onevsrestclassifier and now i want to use onevsoneclassifier. ...
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How many outputs for CNN when dealing with a multi-label classification problem with OneHot Encoded labels?

My labels are of type tensor [1 0 0 1] denoting a 4 label multiclass problem for any given 16x16 image. I'm using BCEWithLogitsLoss from ...
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1answer
258 views

MultiLabelBinarizer() with inverse_transform()

I have multilabel labels. Elements in a label mean voting. Here is how labels look: ...
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2answers
39 views

How to solve this classification problem: multi-class or multi-label?

In a supervised cancer classification task which is given the data containing metrics we want to classify whether the patient has cancer or is at high risk (label 1) or low risk (0). However, there is ...
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55 views

Multilabel Classification - Overfitting?

My task is the following: To input drug combinations and output renal failure-related symptoms from the drug combinations. Both the drug combinations and renal-failure related symptoms are represented ...
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2answers
108 views

How can I label (predict) an unseen set of data based on an existing model?

I'm working on a learning multi-label classification project, for which I've taken 16K lines of text and kind of manually classified them achieving around 94% of accuracy/recall (out of three models). ...
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50 views

Improving misclassification for one class in a multi-class classification task

Here I am trying to use 3 convolution layer neural network to classify a set of images (train data: (3249) , validation data: (487), test data: (326)) I have one class which is misclassified and I ...
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1answer
31 views

Is it better to have one model with more categories or less with two for multi-label classification?

For classifying text into three classes question, complain and complements where each sample can have multi-labels (question and complains, question and complements): is it better to have one model ...
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63 views

Positive/negative training sample imbalance in multi-label image classifiers

I'm trying to train VGG-16 on the Pascal VOC 2012 dataset, which has images with 20 labels (and a given image can have multiple classes present). The examples are highly imbalanced, so I've "...
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1answer
25 views

Is there a deep learning method for 3D labels?

As the question says, I want to feed labels into a neural net that are three dimensional. Let's say that I have 3 possible labels and each one of my data points corresponds to a percentage of those ...
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20 views

Why Overfitting sometimes appears when compile model multiple time, is it normal?

At the time I got small datasets of brainwaves (EEG) (105 samples) for 3-class classification problem. I split my data into 3 part: Train data = 90 (data) Validation data = 10 (data) Test data = 5 (...
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3answers
103 views

Evaluating a Multi-Label Classification model

I currently have a multi-label classification problem, for which I am using keras to build a neural network as follows: ...
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1answer
32 views

Multiclassification with large number of labels

I am attempting to build a classifier with a large input space of one hot encoded vectors. The output should be a vector of labels, with 10000 possible labels each. For example, the labels could ...
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1answer
35 views

Can reducing the number of classes in multi-label classification increase performance?

This is more of an open question with people which have experience in this. I'm working on a multi-class multi-label classification for chest x-rays. I would like to know how much can reducing the ...
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1answer
39 views

Reframing multilabel classification with imbalance in “both” directions

Consider the multilabel problem when asking "does the sample belong to this class" with, for example, a movie label dataset where almost every movie is labelled "drama" because of ...
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2answers
29 views
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1answer
26 views

how to classify text based on more than one column

I passages of text to classify by topic. I am using scikit learn, e.g. linear svc, but open to other options. Currently, use only the text of each passage (column labeled ...
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2answers
73 views

How to divide a dataset for training and testing when the features and targets are in two different files?

I am trying to divide a dataset into training dataset and testing dataset for multi-label classification. The datset I am working on is this one. It is divided into a file which contains the features ...
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1answer
51 views

Classification model to classify large number of classifiers?

Hello I am very new into the field of machine learning/deep learning , and I am finding it hard to select the right model for my research. What I am trying to build is a model to classify which ...
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363 views

multi-label prediction with pySpark

I am new to Spark I am using pyspark to predict a multi label results. I have converted multi labels to binary So my labels will look like this ...
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41 views

SKLearn NearestCentroidClassifier score with predict_proba

I'm using the NearestCentroidClassifier combined with TF-IDF for classification of documents. The are linked to a growing number of document groups. I've set sklearns TfIdfVectorizer and the ...
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74 views

Using pos_weight with BCEWithLogitsLoss to improve recall in a multi-label problem

I have a multi-label classification problem, and so I’ve been using the Pytorch's BCEWithLogitsLoss. I’d like to optimize my model for a higher F2 score, and so want to bias it to have greater recall (...
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1answer
71 views

Random Forrest Sklearn gives different accuracy for different target label encoding with same input features

I'm using sklearn Random Forrest to train my model. With the same input features for the model I tried passing the target labels first with label_binarize to create one hot encodings of my target ...
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Doing q individual train/test splits for q possible labels in a multilabel problem?

Let's say that I have a multilabel problem, where each sample can be of class A, B, C, or any combination of these. Because of high imbalance, I've found that if I tackle the problem as 3 separate, ...
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1answer
319 views

Time Series Data Multi-Class Classification

This is a very general question, as I'm still very much in the learning phase with machine learning. I have some utility data around problematic meters. Even tho the data is "time series", I believe ...
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40 views

How to explain a stable NDCG@K in extreme multilabel recommender model

I am working in a multilabel recommender project and I try to evaluate it as a ranking problem. I calculate recall@k and precision@k which both looks quite well. Recall increases and Precision ...
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1answer
92 views

TensorFlow Time Series Tutorial Enhancement Gone Wrong

I’ve been following this time series tutorial for Tensorflow… https://www.tensorflow.org/tutorials/structured_data/time_series And it was going good, and seemed to work ok. I substituted with my ...
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283 views

What is the better way to predict classes for the models developed using the functional API in Keras

We can predict the class for new data instances using the Sequential classification model in Keras using the predict_classes() function. What is the way to predict the class for models that developed ...

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