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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Sequence multi-class classification only learns a few outputs

I have a multi-event delineation problem, where given a signal, I have an output with the same signal length. Something like 0011002200, where each unique number ...
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Best ML approach for huge number of classes

I have an problem where the dataset consists of: 400k observations 40k classes (mutually exclusive) The problem is about predicting what is the supplier of an invoice (from which supplier/shop a ...
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Train and Validation Curve

I'm new in DeepLearning. I'm not good at understanding and commenting on graphics.Can you help me with these graphs
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What's the difference between multiclass categorical crossentropy, mlogloss and multi:softprob?

As far as I understand, an objective is something I'm trying to optimize and an evaluation statistic is something I use to look for overfitting. I stumbled upon 4 losses that seem to be the same, but ...
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Multiclass classification problem with multiple targets to be predicted

We have a supervised multi-class classification problem where we need to predict two targets for each sample: 'brand' and 'category'. Our features are 'shop_name' which can be any proper noun and ...
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Gaussian Mixture Implementation and Optical Recognition of Handwritten Digits Data Set

Trying to implement Gaussian Mixture model implementation in python using the Optical Recognition of Handwritten Digits Data Set which consists of 10 training folds each of size $\left[100x64\right]$, ...
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How to select the significant cross-terms in logistic regression?

I have data where the number of feature vectors and the number of target classes are identical. I built a logistic regression model to learn the class of unseen data using training feature vectors ...
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How do you do 1-vs-rest classifiers in XGBoost Library (Not Sklearn)?

I am working with a very large dataset that would benefit from using training continuation with the xgb_model parameter in ...
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32 views

How to compute f1_score for multiclass multilabel classification

I have used one hot encoder [1,0,0][0,1,0][0,0,1] for my functional classification model. The predicted probabilities for test data ...
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one hot encoding target variable in tree and non tree (knn) methods

I am learning about label encoders, one hot encoding etc applied to datasets for classification via KNN and XGBoost type trees. However, I am a bit confused as to whether the target variable should be ...
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Evaluating model with categorical target variables

I converted all the numeric target variables of MNIST dataset into categorical variables. So, 0 became zero, and so on. Next, I ...
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How to improve LSTM accuracy on multiclass text classification?

So, I'm trying to build a LSTM model to classify multiclass text label. The goal is to make a prediction about user rating (1, 2, 3, 4, 5) based on their review. My hyperparameter is like this: ...
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Classification Based Collaborative Filtering Model

I was going through algorithms for collaborative filtering-based prediction. Most of the places, I read about using matrix factorization based on ratings of the likeness of the user. But for my use ...
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How do you perform multilabel classification that is also a multiclass problem?

I have a data set in which each row of data belongs to certain classes/labels. text class1 class2 class3 text1 pos neg na text2 na neg na text3 na neu na text4 pos neg neg text5 neg neg na ...
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Help with Classification using scikit-learn models [closed]

I'm using the Titanic data set to classify the missing Cabins. There is a lot of missing Cabin values. My objective is just to assign the letter of the Cabin without the room number. So, I'm just ...
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Theoretical question around multiclass classification

Assume there's a customer dataset with monthly installments repaying goods purchased in advance. The objective is to build a model predicting who is going to be bad debtors and who can afford to buy ...
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Is there an advantage to use decision trees in OneVsAll than using “classical multiclass trees”?

I wonder if the is cases where it's better to use OneVsAll decision trees for multiclass classification ? I think that maybe it could be better for explainability of the model, but I didn't see ...
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Suitable metric choice for imbalanced multi-class dataset (classes have equal importance)

What type of metrics I should use to evaluate my classification models, given that I have two imbalanced multi-class datasets (21 and 16 classes, respectively) where all classes have equal importance? ...
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For multi-class classification in SGDClassifier how do I tell if it is using one-vs-rest or one-vs-one by default?

According to the Geron book, for multi-class classification, SGDClassifier in scikit-learn uses one-vs-rest. But how can I tell which one is used as it doesn't ...
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Validation Accuracy not going beyond 60% for image classification with 5 species of snake

My dataset has about 17000 images belonging to 5 classes. I am using 16000+ images for training(about 3k/class) & 500 for validation(100/class). Training accuracy is very good but validation ...
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Classification algorithm that only matches trained examples

I have 10 categorical features and a multi-class target. Training data contains rows where the same 10 categorical features may map to a different target class. What classification algorithm should I ...
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What kind of approach should I apply for face validation with using deep learning? [closed]

My research task is face recognition in cars with using deep learning method. Actually, in example we set an driver randomly and then the question is: Is this person driver or not? So i created an ...
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Looking for feedback on a semi-supervised learning approach for multi-class classification

Problem: Currently only have 1200 labeled (3-classes) customers with an entire customer base of 4.7M. Just leveraging the 1200 to train the model isn’t generating sufficient results so I’m now looking ...
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Reduce multiclass classification targets to binary classification targets in scikit-learn

I would like to reduce multiclass classification targets to binary classification targets. Ideally, this mapping would happen within scikit-learn so the same transformation applies during both ...
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What is different between R2 and mean of R2 in multiclassification probelm? Which one is correct?

I have a question. I have a big dataset (unfortunately confidential). What I did? I have trained my model with Naive-Bayes. ...
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Apply error analysis on the iris dataset for a specific type of misclassification

Suppose that I have the well known iris dataset and I want to perform error analysis on the misclassified examples, more specifically for a specific class. I don't ...
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Multiclass Classifier comparison decision regions

How can I get the very same effect of this tutorial in Scikit Documentation with more than 2 classes? Let's say we'll keep only the first dataset (the linear separable one) and substitute it with <...
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Designing a network for multiclass regression

I'd like to model a continuous conditional probability distribution for two classes on a given data set. eg the height of men and women from a set of inputs. I can train a regression model (DNN, CNN, ...
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23 views

Best Loss function to use for Multiple Categories which have an implicit order

I am wondering what options I have for loss functions when the task at hand is Multi-Class Classification, where the classes themselves have an implicit order, ranging from least popular (class 0) to ...
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34 views

Sound Classification for Multiple Classes for English Letters

I have recorded audio files for the English letters, each file includes 26 letters. I have split each letter into a separate audio file. Now I want to put similar audio letters into one folder. I can ...
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43 views

Semantic segmentation of an image with multiple labels per pixel

I am building a model for a multiclass sematic segmentation of a skin disease. At a moment I am using U-Net for binary classifications. In this multiclass problem I have the following cases. There are ...
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Math of Logistic regression cost function

In the current scikit-learn documentation for binary Logistic regression there is the minimization of the following cost function: $$\min_{w, c} \frac{1}{2}w^T w + C \sum_{i=1}^n \log(\exp(- y_i (X_i^...
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18 views

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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Is my LSTM model overfitting or underfitting?

I am currently working on a project to classify comments text into 11 different topics, using a Bidirectional LSTM model. However, the loss curves confuse me as there is a deviation of the training ...
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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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39 views

How to calculate the different metrics for multi class classification

My confusion matrix has the following structure: (Predicted) C= ( actual) [TN FP FN TP] How can I calculate the Mathews ...
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25 views

Rolling window on uneven time series classification

I have a univariate time series data that I would like to take about 60 seconds of, extract features using tsfresh and classify into multiclass. So I might end up with a dataframe like: ...
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How can I fix my classifier only predicting two classes, and do my metrics show that it is overfitting?

I have a relatively simple 16 feature neural network attempting to predict the outcome of a sports event as win, loss, draw, however regardless of the number of layers, or the number of nodes in said ...
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Is 50% accuracy on a 4 label multiclass classifier good?

As the title says, I have a classifier with 4 labels. I am having trouble getting much above 50% accuracy in Predicting labels. I made sure the data and test sets are made up of approximately 25% of ...
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30 views

OneHotEncoding target variable? [duplicate]

I'm working on a multiclass classifier with 6 classes on the target column and I was thinking about Hot Encoding the classes, thus having 6 target columns. Will this improve efficiency? I am using <...
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2answers
129 views

Multi-class classification with extremely small dataset

I am working on a text classification task that contains 216 labeled paragraphs. The distribution of tags is as follows: {0: 17, 1: 15, 2: 16, 3: 9, 4: 10, 5: 18, 6: 24, 7: 9, 8: 33, 9: 38, 10: 27}. ...
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How do I handle class imbalance for text data when using pretrained models like BERT?

I have a skewed dataset consisting of samples of the form: Category 1 10000 Category 2 2000 Category 3 400 Category 4 300 Category 5 100 The dataset ...
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1answer
56 views

How to split up my dataset in a train and testset, in order to prevent data leakage?

I realize that this could be considered a duplicate of this question, Is using samples from the same person in both trainset and testset considers being a data leakage?, where it is stated that "...
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1answer
92 views

Machine Learning - Precision and Recall - differences in interpretation and preferring one over other

I have summarising this from lot of blogs about Precision and Recall. Precision is: Proportion of actual positives that classifier has predicted as positive. meaning out of the sample identified as ...
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Classfication report

I have a simple question about classification reports and validation generator in keras. In my case each number in valid_generator.classes corresponds to an artist. But how do i know which number each ...
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Non-uniform class occurances in input data for classification task - how to tackle it?

So, I gathered political articles for my thesis, now I want to be able to classify given text. Though the classes distribution is actually crazy. Class 1: 964 docs Class 2: 37,020 Class 3: 640 Class ...
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38 views

Labels as features in anomaly detection

I have a dataset born to solve a classification problem. Due to the imbalances of the Y, i choose to move to an anomaly detection task. Should I use the Y i have inside the anomaly detection model as ...
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How many instances should be synthesized for each class when using over-sampling techniques?

As for an imbalanced multi-class dataset, how many instances should be synthesized for each class if we use over-sampling techniques such as SMOTE? For example, there is 4 class including 'A', 'B', 'C'...
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311 views

Micro Average vs Macro Average for Class Imbalance

I have a dataset consisting of around 30'000 data points and 3 classes. The classes are imbalanced (around 5'000 in class 1, 10'000 in class 2 and 15'000 in class 3). I'm building a convolutional ...

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