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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Data transformations in hierarchical classification

I am building a hierarchical text classifier using the Local Classifier Per Parent Node (LCPN) approach with the 'siblings' policy as described in the A survey of hierarchical classification across ...
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Classify driver based on time-series sensor data

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
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5 votes
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Why does CV yield lower score?

My training accuracy was better than my test accuracy, hence I thought my model was over-fitted and tried Cross-validation. The model further degraded. Is that my input data need to be sanitised ...
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What does it mean that classes are mutually exlcusive but soft-labels are accepeted?

The Tensorflow's documentation of softmax_cross_entropy_with_logits: Measures the probability error in discrete classification tasks in which the classes are mutually exclusive (each entry is in ...
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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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3 votes
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User actions sequence classification

I have a training set where each row is a series of user actions on a website (logged in, sent an invoice, etc.) and times deltas in ms between these actions. Each row has a label — a corresponding ...
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3 votes
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Can I turn any binary classification algorithms into multiclass algorithms using softmax and cross-entropy loss?

Softmax + cross-entropy loss for multiclass classification is used in ML algorithms such as softmax regression and (last layer of) neural networks. I wonder if this method could turn any binary ...
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382 views

Adjust class weights due to class imbalance and class importance Multi class classification XGBoost

With respect to this question and the answer given by @Esmailian, Would anyone be able to let me know if Class B has a higher importance or the positive class ( i.e. it needs to have a higher ...
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3 votes
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469 views

Deep CNN with variable number of classes and "vanishing" data

I am using a deep CNN to predict the class an image belongs to (N classes). However, the number of classes is not stationary. I.e. over the time the network will be used, some new classes may emerge ...
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why the accuracy of LDA model is always changing and also is high

Let’s explain the whole goal firstly, then go through the question. I am using topic modeling like LAtent Dirichlet Allocation and NMF to extract the topic from a collection of documents. My dataset ...
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How to mitigate the hierarchical error propagation in tree-structured classification

Suppose we have a multi-class classification problem, where the number of classes $K \geq 3$ We use a tree structure of multiple SVMs to divide and conquer the problem, with one example in the figure ...
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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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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

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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2 votes
1 answer
129 views

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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53 views

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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34 views

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 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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2 votes
2 answers
48 views

Basic Machine Learning Question, Looking at where to start

Was recommended to post here instead of StackOverflow I am looking to do some ML, and I just need to know the words to start going off and which library/path to go down. I have two data sets that look ...
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2 votes
1 answer
356 views

Identify optimal thresholds for one-vs-one/one-vs-rest ROC-curve for multiclass classification

Say I have a multiclass classification problem with N classes. I have trained a classifier on a training set, I use a validation set and a One-vs-rest ROC-curve to ...
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2 votes
1 answer
50 views

Comparing Multiclass classifiers with "No Answer"-Class

I have three classifiers to classify some words into four classes. Every word that does not fit into any of these four classes gets classified as "No Answer". I would like to compare the ...
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2 votes
0 answers
94 views

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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2 votes
1 answer
46 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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2 votes
1 answer
72 views

Binary + Neutral Classification

I have a dataset of posts for sentiment analysis that are labelled with -1 (negative), 1 (positive) or 0 (neutral). So I wonder how should I deal with that. These are my ideas: make a multiclass ...
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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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2 votes
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1k views

AUC on ROC Curve near 1.0 for Multi-Class CNN but Precision/Recall are not perfect?

I am building a ROC Curve and calculating AUC for multi-class classification on the CIFAR-10 dataset using a CNN. My overall Accuracy is ~ 90% and my precision and recall are as follows: ...
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2 votes
2 answers
90 views

Keras deep learning speaker identification model excels during training and then fails predictions

I am attempting to create a 1:N speaker identification model with Keras using a TensorFlow backend. I used the LibriSpeech corpus for training data, and preprocessed the data by first converting each ...
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2 answers
146 views

How to train a machine learning algorithm with multiple labels

I have the following challenge and I very much hope that there is a solution to it. I also suspect that there is a simple approach to it. I just don't see it at the moment. Any help or advice is ...
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2 votes
1 answer
1k views

Generate a balanced batch with ImageDataGenerator() and flow_from_directory()

Hi I am new to python and deep learning. I am doing a multiclass classification. My 3-classes dataset is imbalanced, the classes take about 50%, 40%, and 20%. I am trying to generate mini batches with ...
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2 votes
2 answers
71 views

Multiclass classification task where each class is present only once in the test set

I have a multiclass classification problem where, in the test set, there is only one entry for each possible class. In my particular problem we want to guess the author of a text, and we have 20 ...
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2 votes
1 answer
213 views

How to estimate the accuracy on a large dataset?

Given that I have a deep learning model(handover from former colleague). For some reason, the train/dev set was missing. In my situation, I want to classify my dataset into 100 categories. The ...
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2 votes
1 answer
163 views

Use cross entropy to create decision tree classifier

Are entropy and cross-entropy the same thing as per the basic definition? If there is a difference: Decision tree splits take on entropy or Gini index, can we use cross-entropy to split decision trees?...
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2 votes
1 answer
111 views

Co-joining multi-peak histograms

I am analysing a bunch of data files which represent responsiveness of cells to addition of a drug. If a drug is not added, cell responds normally, if it is added, it shows abnormal patterns: , . We ...
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2 votes
0 answers
24 views

Does object detection do a better job at image classification than image classification

I read in an article that object segmentation can do object detection better than object detection algorithms. I assume this is because there is more detailed information in the annotation images. I ...
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2 votes
1 answer
270 views

Which model to use for multiclass audio classification?

I am working on a project wherein I want to classify Tabla taalas(patterns) and I didn't find any dataset regarding it. I am recording them myself and I've ~500 data samples recorded. What model shall ...
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2 votes
0 answers
767 views

Can McNemar's test be applied to evaluate multiclass models?

Full Disclosure: I did a semi-cross post of this question due to low traffic on Cross Validated. Once I get an answer on any of the two questions, I will link the answer back to the respective other. ...
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2 votes
0 answers
854 views

Hierarchical classification with multi-class predictor for every parent node

Edit: It turned out that I had an error in my function to compute the combined probabilities (a typo that changed the behavior of my function quite a bit without giving me an error message). Without ...
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2 votes
0 answers
37 views

Multiclass classification problem with more prediction classes than real classes

Can I have a multiclass classification problem with more prediction classes than real classes? For example: I want to predict the channel the user is going to watch. The real classes are "user didn't ...
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2 votes
2 answers
2k views

Solving multi-class imbalance classification using smote and OSS

I am trying to solve a multi-class imbalance classification problem. For that, I am using SMOTE for oversampling and OSS for under-sampling. But I have a doubt as I am working on multi-class so I have ...
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2 votes
0 answers
569 views

Sample size equation for multi-class distribution

I have a large (k>15) number of potential classes involved in a text classification problem, and don't know the true distribution of these classes in the ...
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2 votes
1 answer
88 views

Unbalanced multi-class : distribution might change as more data come in

I am currently working on a problem of multi-class classification on testing logs data. Basically, I have the context data from tests' execution saved, and want to automate the analysis of the ...
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2 votes
0 answers
377 views

multi class classification : unbalanced data - good testing results poor prediction results

I have unbalanced dataset with 11 classes where 1 one class is 30% and rest are between 5-12%. I am not a hardcore programmer so I am using the product from https://www.h2o.ai/. I used GBM and DRF ...
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2 votes
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503 views

How to plot calibration curve for multi-class problems?

How to plot calibration curve for multi-class problems, for example the available example on python plots it for 2 classes but here in the e-book link it is done for multi-classbook how can I do so ...
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212 views

Train a multi-output neural network to learn subset of "valid" response combinations

I'm working on extending a model of human immediate serial recall task performance, originally described in this paper. This model takes a sequence of items, such as digits or phonemes, stores them as ...
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2 votes
0 answers
548 views

Fisher's Iris data set with Caffe

I am trying to use Caffe on the usual Fisher's Iris data set (150 flowers, each having 4 features, and split into 3 classes): if a flower belong to class 1 (setosa), the network output should be [1, ...
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1 vote
0 answers
16 views

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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1 vote
1 answer
26 views

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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