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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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77 views

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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1answer
76 views

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 ...
4
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1answer
226 views

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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0answers
75 views

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 ...
4
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1answer
702 views

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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2answers
61 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 ...
3
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1answer
110 views

Unbalanced data set - how to optimize hyperparams via grid search?

I would like to optimize the hyperparameters C and Gamma of an SVC by using grid search for an unbalanced data set. So far I have used class_weights='balanced' and selected the best hyperparameters ...
3
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1answer
58 views

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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0answers
185 views

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 ...
3
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0answers
354 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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0answers
441 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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0answers
1k views

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 ...
2
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1answer
29 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 ...
2
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0answers
45 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 ...
2
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1answer
38 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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0answers
24 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 ...
2
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0answers
37 views

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 ...
2
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0answers
529 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: ...
2
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1answer
40 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 ...
2
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1answer
147 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 ...
2
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1answer
110 views

Use cross entropy to create decision tree classifier

Are entropy and cross-entropy the same thing as per 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? ...
2
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1answer
21 views

Statistical test using Gmean to compare multiple algorithms on multiple datasets

I am new in this area. I am facing some issues while comparing the algorithms using statistical test. I have following result of Gmean of some classification algorithm. Abalone, Balance-scale, Car, ...
2
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1answer
93 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 ...
2
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0answers
23 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 ...
2
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1answer
234 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 ...
2
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0answers
515 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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0answers
672 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 ...
2
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0answers
34 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 ...
2
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2answers
2k views

solving multi-class imbalance classification using smote and OSS

I am trying to solve 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 to ...
2
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1answer
83 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 ...
2
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0answers
342 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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0answers
458 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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0answers
211 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 ...
2
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0answers
112 views

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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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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15 views

Precision and Accuracy of a custom Object Detection Models usind networks from TensorFlow Model Zoo

I am trying to develop a model with three classes. To do so, I tried to develop a model with different combinations of the data samples in each class. For example: the $1^{st}$ model has 500 images ...
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1answer
33 views

Handle with very short and very long sequences with Neural Network

I am working on multi-class problem with sequences. My dataset is composed of sequences of data with different length. E.g. 1500 labeled samples: 500 datapoint belongs to class A, 500 class B and 500 ...
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1answer
33 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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0answers
17 views

Dependent variable with very few distinct discrete values

I've been reading about different ways to produce models for a dependent variable that has very few distinct discrete values, but haven't found the right fit. I was thinking of using an ordinal logit ...
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0answers
39 views

LSTM Many to one with multiple time steps for time series (multi class classification)

I want to do a time series multi-class classification for fault detection and diagnosis with time-series sensor data set which contains a sequence of 50 records of normal data and sequences of another ...
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0answers
17 views

What is the appropriate statistical test to compare the MAUC scores from two machine learning classifiers?

I would like to compare the scores of two multi-class classifiers. I have calculated the MAUC score for each of the algorithms, and now I want to see whether there is a statistical difference between ...
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1answer
70 views

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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1answer
50 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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1answer
97 views

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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0answers
20 views

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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0answers
36 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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0answers
154 views

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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0answers
28 views

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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1answer
41 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 ...
1
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1answer
42 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, ...