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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Multiclass classification (gradient boosted trees) predictions distribution using softmax()

Let's consider a multiclass problem where the target is composed by 20% class 'A', 50% of class 'B' and 30% of class 'C'. The model is trained and then the class predictions are obtained via the ...
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Which model to use or how to preprocess the multi-dimensional data to classify?

I've a dataset containing only numpy arrays, without description on features. About 2k rows and 0.7k features. Divided into 1.4k train and 0.6k test. Applied baseline SVM and get F1 score of around 0....
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Should training images contains single or multiple object instances?

I'm pretty new to ML so I apologize for the potentially trivial question; I've been unable to find a clear answer to my question. Let's imagine that I want to build a model that is able to detect ...
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Is there a way I can double the punishment when model mis-classing to a specific class?

As the title I asked. For example: a model that predicts the probability of a stock price rising/falling. Let's say this is a triple-classification problem. If it predicts "RISING", while ...
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Imbalanced multiclass classification using keras

I have a multi-class classification problem with imbalanced dataset, I'm trying to solve this problem with multilayer perceptrons using keras. And I have assigned wights using the class_weight ...
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Classification problem with too many classes and requiring specific outputs

I'm trying to solve this exercise in which I have around 10 thousand rows of data with 6 columns of features and one column with over 3 thousand targets. The problem says I need to program an ...
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Weighted Classification Metric for Multi class classification

I have a multi-class classification problem with the classes X-Small, Small, Medium and <...
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Classification on severe Class Imbalance high dimensional data

Dear DataScience Community, I am working on class imbalance tabular data with high-dimension inputs. The tabular data is derived from the satellite data pixels, and I have inflated the train data ...
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My model is predicting values ​for only two labels (instead of 9) how to fix it?

My goal is to predict the count (variable y) based on various features (variable x). My y is most of the time (98.4%) equal to 0, so this data is inflated by 0. Based on this premise, I thought that ...
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The paradox of Imbalanced binary classification ¿To do something or to do nothing?

Context: Suppose we are interested in deploy a machine learning model to solve a problem of binary classification; furthermore, assume that the dataset $\mathcal{D}$ for the training of our model ...
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What is the benefit from going from unordered to ordinal classification?

Let us assume that we have naturally ordered data that we want to classify. Then we can use ordinal regression/classification methods. Yet we can treat those as unordered and use multiclass ...
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Equal error rate for multiclass (non-binary) classifier

In many biometrics identification papers they measure they performance by computing Equal Error Rate (EER). When dealing with verification problem, or any other binary classification problem - the ...
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Multivariate timeseries classification for each group in a dataset

Let's say, I have the following dataset: ...
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How to choose a machine learning sampling method?

I have a multiclassification problem with a training dataset of 3 groups (50 samples:150 samples: 100 samples). I have tried comparing models running SMOTE oversampling and class weighting (using ...
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Multi classification problem with unique target labels

I would like to know if it is possible to predict values that are not repeated (unique) in my dataset. Example: In this example let's say my features are [Price, velocity] and target variable is: [Car]...
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Dealing with variable length videos where frames are multi class in Keras' temporal convolutional networks (TCN)

I am working on an action segmentation problem whereby I have multiple videos of different lengths containing several actions. I have created features for each video which are also of variable length. ...
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Hierarchical Dependent Multilabel Multiclass classification

I am aware of both multi-class and multi-label classification. But here is my use case, X1,X2,....Xn ==> Level1,Level2,Level3,Level4,Level5.. Image attached of a contrived example. So the model's ...
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How to predict a class for a file given a small number of files for training?

I have been given the following data: 20 example CSV files, each labeled as belonging to one of six fixed classes, say A, B, C, D, E, F. Each file has roughly 20000 rows and 10 floating point columns....
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What's the difference between micro-averaged precision and accuracy score?

I'm using sklearn's metrics module to try and evaluate a k-NN model's performance on the provided iris dataset from the ...
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Threshold tuning with one-vs-rest for multi classification python

I’m currently using a One vs Rest Random forest algorithm for multi class classification problem using Python, and I want to find the optimal threshold for each class, How can I do this with OVR (One-...
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Biometrics identification with embeddings comparison and "unknown"/"other" class/label

This is a general or more conceptual questions about biometric classification models, based on deep learning neural networks. The goal of the system is to take a set of features (e.g. voice recording, ...
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Each multi-class output has another level of multi-class output

I want to predict a major class and then minor class. Major class is a multi-class model which has 4 categories. Each of this categories has 10-15 subcategories, for which I can build a multi-task ...
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Techniques for classification AI with sparse labels

I want to create an AI to classify images with a large set of labels (1000+ labels). However, the labels in the data set are correct but each image is not fully labelled. This means that each image's ...
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Text2Slide multiclass classification

I am considering an idea of stitching together a slide deck based on text input, e.g. given: ...
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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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