Questions tagged [multiclass-classification]

Multi-class classification is when you have a classification problem with multiple classes, specifically 3 or more classes. Many classifications are binary by design, therefore the additional nomenclature of multi-class classification was defined to describe algorithms capable of classifying datasets with more than 2 classes.

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Deriving a binary logistic classifier from a multi class logistic classifier

Given a multi class logisitic classifier $f(x)=argmax(softmax(Ax + \beta))$, and a specific class of interest $y$, is it possible to construct a binary logistic classifier $g(x)=(\sigma(\alpha^T x + b)...
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How to add class labels to confusion matrix of multi class classification

How do I add class labels to the confusion matrix? The label display number in the label not the actual value of the label Eg. labels = ['A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P',...
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Text similarity for badly written text

Consider the following scenario: Suppose two lists of words $L_{1}$ and $L_{2}$ are given. $L_{1}$ contains just bad-written phrases (like 'age' instead of '4ge' or 'blwe' instead of 'blue' etc.). On ...
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Using Sci-Kit Learn Clustering and/or Random-Forest Classification on String Data with Multiple Sub-Classifications

I have a set of data with some numerical features and some string data. The string data is essentially a set of classes that are not inherently related. For example: ...
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Multi-Label time-series classification with LSTM: large performance decrease for longer periods

I have daily data on event occurences, so for each day I have a vector like [1, 0, 1] indicating that on this day event one and three occured, but event two did not occur. I want to train a model to ...
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Binary classification from local and global feature selection

I want to train a deep leaning model, consisting of images. My question is which scenariowas chosen to train the model? scenario 1 : I train images local context on Output 1, and I train images clobal ...
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Using CNNs to detect incorrect label images in dataset

What I want to do is to train a model to identify the images that are incorrectly labeled in my dataset, for example, in a class of dogs, I can find cats images and I want a model that detects all ...
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Language Detection using pycld2

I am trying to use the pycld2 package to detect multiple languages in text. This package provides Python bindings for the Compact Language Detect 2 (CLD2) This is the example I am testing out: ...
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Suggestions for a multi-class text classification model with a large number of classes?

I was working on a text classification problem where I currently have around 40-45 different labels. The input is a text sentence with a keyword. For e.g. ...
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How to get all the parameters of scikit-learn multiclass SVM classifier?

I have trained my multiclass SVM model for MNIST classification in Python using scikit-learn using the following code: ...
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Low classification accuracy

I want to do a multi class classification with 6 classes. Whole dataset has 12750 and 56 features samples, so every class has 2125 samples. Before prediction I reduces amount of outliers by ...
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Text to Text classification

I am new comer to the field of data science and have been struggling with a simple classification problem. It seems to be generic enough and I have a suspicion that there must be a better way to frame/...
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how to deal with large numbers of unlabelled target dataset?

I have dataset of 5000 jobs descriptions out of which only 200 jobs are labelled with required English level score range between 0 to 9 and I want to predict remaining 4800 jobs required English level ...
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How much ground truth is needed for a classification model?

I have unstructured problem text that needs to be classified into categories(Multinomial classification). Depending on the component, which is a structured element that allows me to segment the data, ...
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1D Sequence Classification using Circular Dilated Convolutional Neural Networks

I am working on a multiclass classification task on long 1D sequences. The sequence length may vary between $512$ and $512 \cdot 60$ timesteps, a slice of $100$ timesteps might look like this: What ...
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What is the good way to print classifier lines with sklear learn LinearSVC

I've tried to make a multivariate regression with LinearSVC and I have seen two ways to print the lines of the classifier, and they haven't the same output. I have seen one on this forum and the ...
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1D Sequence Classification

Cross-post from https://stackoverflow.com/questions/71752744/1d-sequence-classification I am working with a long sequence (~60 000 timesteps) classification task with continuous input domain. The ...
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How do I use wavelet transform for feature extraction correctly?

I'm trying to classify words based on EMG signals using a support vector machine as my model. My dataset includes 15 classes (words) with 230 repetitions and 1000 features each. I already merged all ...
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Multi-Class Document Classification with both known and un-known classes

Currently, I am building a multi-class document classifier which has to classify either 3 known classes, namely "Financial Report", "Insurance_Sheet", "Endorsement", and ...
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Commercial product name classification with product id

I want to give the probability of how the entered name (user 1) for product X matches with the names (historical names from all users) of product X. I have data with the following structure: while ...
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Classifying two classes when having noise as a third class

Say I have a dataset of e-mails and I want go classify the newsletter and news emails. One way to do so, is to take all the ...
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spacy multi label classification help

I would like to create a multilabel text classification algorithm using SpaCy text multi label. I am unable to understand the following questions: How to convert the training data to SpaCy format i....
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Decide threshold for each class for optimal precision/recall in a multi-class classification problem

Say I have three classes $C_1$,$C_2$, $C_3$ and a model $M$ which outputs a score $P$ for the confidence of each class for a sample $X$ i.e $M(X)=[P(C_1),P(C_2),P(C_3)]$ (note, we only want to predict ...
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Classification using STFT for multiple categories of signal samples

I have a collection of signals (IQ wav) split up into ~2s samples of sampling rate 2MHz, and can collect the STFT information from these samples through the following code: ...
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'list' object has no attribute 'lower' TfidfVectorizer

I have a dataframe with two text columns and I converted them to a list. I seperated the train and test data as well. But while making a base model TfidfVectorizer throws me an error of 'list' object ...
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Find optimal feature combinations and ordering for a multi-class clasification problem

We have a multi-class classification problem where the training data looks as follows: name A B C brand Snickers Ltd company huge sales Snickers Acme Intl office stationary commercial Acme ...
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Can we recognize different events in time-series data by patterns?

I'm currently have to deal with multiple time-series datasets with the same type of patterns. My quest is to find a way to label these data points (or may be intervals) correctly. Below is how the ...
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2 votes
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A multi label text classification problem

I'm looking to solve a multi label text classification problem but I don't really know how to formulate it correctly so I can look it up.. Here is my problem : Say I have the document ...
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Train/predict a classifier when the data contains more classes than we want to predict

(I don't know how to phrase the title thus feel free to suggest another title). Say I have dataset which contains images of dogs,cats,birds and other animals, and I want a classifier which only ...
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2 votes
1 answer
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ROC_AUC score is higher before tuning n _neighbors for KNN

This is for multiclass classification. Before tuning the n_neighbors for KNN, these were the results: ...
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Is there a methodology or framework for when you want to do multiple classification model runs introducing predictor variables sequentially?

I have a cohort of ~20 schoolkids and I want them to perform a sequential order of 7 tests for a competition. The scores for the tests have an average score will be around, say, 60 to 80 for each test....
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how to visualize segmented labels in a already existing graph?

I am working on a project where I have to segment the image using multi-class segmentation (3 classes) on microscopic images. Now let's say that I am segmenting solid, liquid and gas images (this is ...
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Predict feature against specific labels among set of labels in multi-class classification

I have the following code in keras for multiclass classification: ...
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Class imbalance: Will transforming multi-label (aka multi-task) to multi-class problem help?

I noticed this and this questions, but my problem is more about class imbalance. So now I have, say, 1000 targets and some input samples (with some feature vectors). Each input sample can have label ...
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ValueError: `class_weight` is only supported for Models with a single output

I'm getting the below error while using class weights in the model.fit in tensorflow version 2.7.0 ...
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Xgboost Multiclass evaluation Metrics

Im training an Xgb Multiclass problem, but im having doubts about my evaluation metrics, heres my code + output ...
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I have keras model for predicting emotion and it gives same output for all inputs(im currently new to deep learning))

...
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How Should I Create Waveform Datasets

Full disclosure I asked this on StackOverflow and it got taken down as it was more of a how do I do this, not how do I code this question: I am trying to simulate/fake data that I eventually will ...
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2 answers
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Evaluation Metric for Imbalanced and Ordinal Classification

I'm looking for an ML evaluation metric that would work well with imbalanced and ordinal multiclass datasets: Imagine you want to predict the severity of a disease that has 4 grades of severity where ...
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Which will be best deep learning model for topic classification using NLP [closed]

I have a dataset consisting of two columns [Text, topic_labels]. Topic_labels are of 6 categories for ex: [plants,animals,birds,insects etc] I would like to build deep learning-based models in order ...
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Transform multi-class problem to multi-label problem

I found this question but I need an answer to the other direction. Example: Let's say we want to predict if a person with a certain profile wants to buy product A and/or B. So we have 2 binary classes ...
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Sentence Classification Machine Learning API

Are there any ML models or APIs that can be used to classify a sentence into one of the four types of sentences; i.e. declarative (statement), imperative (command), interrogative (question) and ...
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Approaches for multiclass classification with a reference level to extract variables of importance?

I have a dataset with with multiple classes (< 20) which I want to classify in reference to one of the classes.The final goal is to extract the variables of importance which are useful to ...
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2 votes
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Classification Texte with naive bayes complement

Currently I am on a text classification project, the goal is to classify a set of CVs according to 13 classes. I use the bayes algorithm (ComplementNB), in my tests it is the model that gives the ...
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Semi-supervised classification with SelfTrainingClassifier: no training after calling fit()

I am practicing semi-supervised learning, at the moment experimenting with sklearn.semi_supervised.SelfTrainingClassifier. I found a dataset for multiclass ...
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Can I replace categorical data with numbers in classification problems?

I am working on classification data that have 9 classes and so many features. well, classes are categorical obviously as well as some features. I used the one-hot encoding technique to transform ...
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1 vote
1 answer
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Clustering text data based on sentiment?

I am scraping reviews off Amazon with the intent to perform sentiment analysis to classify them into positve, negative and neutral. Now the data I would get would be text and unlabeled. My approach to ...
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Should I merge multiple target bins into one for better results?

I have a multiclass classification task where the target has 11 different classes. The target to classify is the Length of Stay in a hospital and the target classes are in different bins, for example, ...
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Which Keras metric for multiclass classification

I have a multiclass classification data where the target has 11 classes. I am trying to build a Neural Net using Keras. I am using softmax as activation function ...
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SMOTE for multi-class balance changes the shape of my dataset

So I have a dataset of shape (430,17), that consists of 13 classes (imbalanced) and 17 features. The end goal is to create a NN which btw works when I import the imblanced dataset, however when i try ...
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