Questions tagged [multi-class]

Multiclass classification is a classification task in which there are more than two classes. It is also called multinomial classification.

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135 views

How to maximize subset accuracy for multilabel multiclass image classification

I working on multi-label multi-class image classification. I am using TensorFlow. Currently I am using sigmoid on output layer with binary_crossentrpy. Model is ...
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324 views

Why not approach the Multi-Class Classification problem using Neural Networks as a model the same way it's approached with a Logistic Regression model

I can't seem to understand why when approaching a K-class classification problem using a Neural Network we take a different approach than any other classification model. I understand that in the ...
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37 views

How high is multiclass AUROC too high?

Whenever I get AUROC above 80% for a binary classification problem I do my best to check for leakage and overfitting - and usually my intuition is right, true AUROC is closer to the 70%-75% range. ...
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16 views

Passive Combination of two Classifiers at the level of Class Labels

I have three classifiers - 1. Vision based classifier trained to detect class labels such as pedestrian and cars 2. Radar based classifier to detect same class labels 3. Lidar based classifiers to ...
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1answer
192 views

Bayes Decision Theory With 3 Classes

I'm trying to create a Bayes classificator in 1 dimension with 3 classes. I have created the following graph, where you can see that from zero to $x_{bnd1}$ is the first area $R1$, then from $x_{bnd1}$...
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1answer
299 views

Why does the 'weighted' f1-score result in a score not between precision and recall?

On the F1 score sklearn page there's a section that explains each of the options for the average parameter. Under the weighted option, it says: "it can result in an F-score that is not between ...
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2answers
5k views

Error while performing multiclass classification using Gridsearch CV

I am trying to solve a multiclass classification problem using SVC as the base estimator and GridSearchCV to tune my results. Mentioned below is the code and the error being received: ...
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1answer
183 views

Is skip-gram model of word embedding actually a multi-class task not a multi-label task, right?

So curious about this question, that I can't describe it in short. Please forgive me. Description: From multiclass and multilabel algorithms, we can get the definition of the multi-class and multi-...
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1answer
90 views

Is it wise to reduce the number of labels in a multi-class classification problem?

I'm working on a dataset which has 5 labels or the outcome, Y. I'm going to use ML model to predict the 5 labels. While doing the data analysis, I found that class1(60%), class2(39%),class3(0.33%), ...
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45 views

Comparing multiclass LDA and logistic regression equations

I was told that LDA and logistic regression is the same, when we consider 2 class situation. That I can also confirm (I think), for LDA $$\log \frac{Pr(Y=1|X=x)}{Pr(Y=0|X=x)} \\ = \frac{f_1(x)\pi_1}{...
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2answers
3k views

Calculate AUC using sensitivity and specificity values only

How to calculate AUC, if I have values of sensitivity and specificity for various threshold cutoffs? I have sensitivity and specificity values for 100 thresholds. ...
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2answers
1k views

Oversampling a multi-labeled data set

Given a data set where each individual data point can be assigned to more than 1 class (a multi-class, multi-label data set), are there any guidelines for calculating oversampling weights, i.e., the ...
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3answers
362 views

Feature selection in multi class environment

I have a $\mathbb{R}^{10000 \times 25000}$ feature matrix (10000 observations and 25000 features). The observations come from 4 different classes, i.e. it is a multiclass classification problem. I ...
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1answer
95 views

multiple measurements for classification; which one to choose?

There are five different classes (labels) where the new points have to be classified at. For each new point, five different measurements are conducted, resulting into similar although different values ...
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19 views

does multicolinearity affect classification models? any type of classification models like SVM, ANN, Random Forest,etc

I have been working on a dataset with more than 50 variables and I know some of the variables are highly correlated(>0.8). so for my multi-class classification problem should I worry about ...
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18 views

Naive Bayes missclassification rate across classes

I have a dataset with income, age sex and education as categorical features. I used R to create a Naive Bayes classifier as follows: income ~ age + sex + education. I got the following a-priori and ...
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Is there any strategy for validating the result of a general comparison between several confusion matrices?

Disclaimer: Recently we have developed a python library named PyCM specialized for analyzing multi-class confusion matrices. A compare system has been added in <...
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469 views

Evaluating Unbalanced Multiclass Classifiers: Which Tests to Use? [closed]

I am looking for some comprehensive instructions and ideally out of the box solutions (ideally for python) for evaluating different classifiers (which are already trained) for a multiclass ...
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1answer
321 views

Improving Average F1 Score for Multiclass Classification

I'm trying to do a multiclass classification with h2o in R. I stacked a model with a RF, GBM and deeplearning. The accuracy is ok (~0.81), but the average F1 score is bad because class B has a very ...
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14 views

What measures of an ML algorithm's 'accuracy' are mostly consistent as the number of classes to predict into varies?

For a research project, I've got a bunch (N=507) of 20-second VR tracking data clips (6DOF x head and hands), each from a different participant. My goal is to predict the participant using a small ...
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1answer
4k views

What is difference between accuracy_score() and cross_val_score()?

The problem I'm working on is a multiclass-classification. Have been reading through lot of articles and documentation, but not able to figure out which of Accuracy_Score or Cross_Val_Score should be ...
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1answer
692 views

Machine learning for product names

I have a machine learning challenge I may be over thinking. I have a set of 3.5 million products (not unique, there are multiple instances of each product). Each product has a "description" from it's ...
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2answers
67 views

Which classification model should I choose and Why?

I am working on a research-based assignment where I suppose to build a 3-class (bad, medium, good) classification using SVM. The dataset provided is imbalanced. The train:test splitting ratio is 75:25 ...
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1answer
236 views

Anyway i can improve this multi class classification result?

I am building a multi class classification model using SVM to predict the grade for essays. What can I do to improve the result especially for class 1 and class 3? Their precision and recall are ...
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1answer
5k views

Adjust thresholds in multi-class classification [duplicate]

I have trained a random forest classifier on a (highly-imbalanced) 3-class problem (A 1% of the data, B 96%, C 3%) and obtained probabilities for each of the three classes. Currently I assign an ...
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1answer
146 views

Quadratic Weighted Kappa metric in H2O package for model performance

I am running a multiclassification problem and before I make a function by myself I was wondering if anyone knows of a pre built quadratic weighted kappa function in the h2o library.
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1answer
2k views

Multi-class Decision Forest vs Multi-class Decision Jungle

guys. I have been learning about machine learning using Azure ML service from Microsoft and my team and I have seen that there are some multi-class decision algorithms, the Forest and Jungle are ...
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2k views

Multi Layer Perceptron and multiclass classification in Python problem

i have a problem regarding MLP in Python, when i am making multiclassification i only take as an output one of the possible 4 classes. I tried a solution of instead using "predict", using "predict....
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1answer
3k views

Imbalanced multiclass classification with many classes

I am working on a text classification project in which we have hundreds of (imbalanced) classes. Some characteristics of the data: We have examples of "bad" documents. Basically documents that don't ...
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0answers
90 views

How to know if your decision tree model has overfitting or not?

I am using the DecisionTreeClassifier() of python and I am changing some tuning parameters to understand if my model has overfitting or no because when I exectue the following code without any ...
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1answer
2k views

Summing predicted probabilities from logistic regression using 'one vs. rest'

I have a multiclass classification problem that I have solved using a 'one vs. rest' approach via binary logistic regression classifiers from Python's scikit-learn package. In my problem, there are 3 ...
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615 views

Simulate/Generate Data for Multinomial Logistic regression

How to simulate data for Multinomial Logistic regression? For Example i want to generate a high dimensional data set with 90 subjects and 500 independent predictors. The ratio of Classes should given ...
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1answer
1k views

How to manually balance unbalanced multi-class/multi-label data?

I have a multi-class and multi-label classification problem, i.e.: each sample can have more than one label associated to it and there is a total number of M ...
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2answers
101 views

Decision tree without the “tree”

I would like to construct something like a decision tree. However, instead of using "recursive partitioning" to build a tree, I would like to find an optimal set of "global" splits. For example, in a ...
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0answers
984 views

How to combine/aggregate classification accuracies from binary one-vs-one classifiers to get final accuracy equivalent a multiclass classifier?

Consider a 3 class data, say, Iris data. Suppose we want do binary SVM classification for this multiclass data using Python's sklearn. So we have the following ...
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1answer
2k views

ValueError: Requesting 3-fold cross-validation but provided less than 3 examples for at least one class. Any way to get away with this? [closed]

I am trying to perform multiclass classification on a 10 class dataset with around 650 data points. But whenever trying to run the code, it gives the above-mentioned error. Although, I understand what ...
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149 views

PR curve and confusion matrix members for multiclass and multilabel classification problems [closed]

I am looking for any libraries which provide out of box support for calculating PR curve and the confusion matrix items(not just count but the items which contributed to the count as well) for ...
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1answer
232 views

For multiclass classification purpose I have to use a imbalanced dataset

I am facing a problem. It's a multiclass classification problem I have 5 categories A has 107 instances B has 101 instances C has 882 instances, D has 229 instances and E has 129 instances. I used Knn,...
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0answers
327 views

Similarity between Train and Test data sets

I have multiclass classification dataset and I am using Deep nets for the classification task. To explain the problem, let's assume that I have 5 classes to classify. No matter what I try, be it ...
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1answer
2k views

Probability calibration metric for multiclass classifier

A machine learning classifier can be calibrated so that when the probability that datapoint i is of class A is 0.6, this is true 60% of the time. In the binary class setting, this can be visualised ...
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0answers
152 views

Introducing “Unclassified” class into a multiclass classifier

I'm trying to multi-class classification problem with a small addition that I can't find a decent way to handle: according to domain knowledge, no classification is better than a wrong classification. ...
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39 views

Keras accuracy not affected by any change in model [duplicate]

I am trying to construct a model for single-label multiclass classification using Keras in a Jupyter notebook. Here's my model (or see full jupyter notebook): ...
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227 views

Multiclass text classification with insufficient dataset

I am working on a multi class text classification dataset which has 2719 data (only training set is available test set is not available) and 256 classes. Sentence length of each data is very short, ...
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35 views

Multilabel classification versus yes/no classification for each class (with label priority)? [duplicate]

NOT A DUPLICATE. These questions are related, but mine is asking about a specific application of classifiers - flagging Stack Exchange posts. I want to know which of the 2 methods is most effective ...
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1answer
370 views

How do you calculate precision and recall for multiclass classification with only two classes?

I'm trying to predict the gender of a Twitter account using only the profile information like tweet text, description and used colors. I've trained a SVM classifier and then tested dividing the ...
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1answer
128 views

Correct feature aggregation for this tricky buying problem

Consider the following problem, which was asked in an interview I was at (but it wasn't directed at me). It seems deceptively simple, but then it turns out to actually be really hard to answer well: ...
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1answer
730 views

multi label misclassification rates

I'm looking for a way to efficiently describe the performance of a multi-label classification model (if possible, something like confusion matrix for the multi-class classification). I'm not sure if ...
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1answer
492 views

Combine two different multi classification models for better prediction

I have two different multi-classification models on the same dataset. Since both use the same dataset, input and output are the same. For example, given input x, model A and B output like the below. ...
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0answers
441 views

Multi-class image segmentation with conflicting labels

I'm trying to perform multi-class semantic segmentation on a corpus made up of several sub-corpora. The difficult part is that across sub-corpora labels are not consistent. That is to say that similar ...
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1answer
4k views

Handle categorical class labels for scikit-learn MLPClassifier

I have a handwritten dataset for classification purpose where the classes are from a-z. If I want to use MLPClassifier, I think I cannot use such categorical ...

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