Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange
Make your voice heard. Take the 2019 Developer Survey now

Questions tagged [multi-class]

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

1
vote
1answer
36 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 ...
0
votes
0answers
13 views

RFE-RF for non-ordinal multi-class problem using integer target variable

For a classification problem with numerical predictors and a categorical multi-class response I am trying to use Recursive Feature Elimination with Random Forests to identfy relevant features out of a ...
0
votes
1answer
22 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.
0
votes
0answers
14 views

Logistic Regression(multi class) accuracy too small

I try to solve a problem with 3 features and 6 classes(label). The training dataset is 700 rows * 3 columns. I use one-Vs-all method, but I do not why the prediction accuracy is too small, just 24%. ...
1
vote
1answer
40 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 ...
0
votes
0answers
41 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....
0
votes
0answers
9 views

Evaluating multiclass decision tree as a probability function

I have a problem where I am trying to estimate the transition probability within a state-diagram. For example, estimating the chances of transitioning from a happy mood to one of 3 possibilities (...
0
votes
0answers
10 views

High accuracy for single classes & low accuracy for multiclass classification

I was trying to do a multiclass-classification, where each sample belongs to one of the four classes. Now that I have a probability vector $(p_1^i,p_2^i,p_3^i,p_4^i)$ for each sample $i$ as my ...
0
votes
1answer
76 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 ...
0
votes
0answers
20 views

What is a good performance index in multi-classification problem?

I'm performing a multi classification model exploiting different statistical learning methods. In particular, I'm performing a classification in 3 different classes. I'd like to know if there exists ...
1
vote
0answers
29 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 ...
0
votes
0answers
22 views

Understanding model performance

I built a multiclass (and very imbalanced classes) classifier. When evaluating I found an average F1 of .98 and the classifier seems to be working rather well. However, on evaluating the ROC and ...
0
votes
0answers
55 views

CNN Flower recognition (5 classes) accuracy improvement

I have created a CNN for image recognition (Flower types - 5 classes) and am now considering model parameter changes to improve accuracy. The model (5 3*3conv + 4 2*2max pooling layers) attains ~60% ...
0
votes
0answers
15 views

How to group text categorical data basis on clustering?

So if I have text dataset where I have more than 50 categories. Sample: ...
2
votes
0answers
21 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 ...
0
votes
0answers
77 views

Classification confidence at Multi-class classifier with Soft-max output

what I'm NOT asking about is : Confidence interval So the question I'm trying to find the answer of would be : how to measure the confidence of a multi-class classifier with a Softmax output (eg a ...
3
votes
1answer
108 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 ...
1
vote
0answers
112 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 ...
0
votes
1answer
49 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 ...
1
vote
0answers
226 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 ...
0
votes
0answers
9 views

Splitting strategy for a multiclass problem

I have a 16 class data , Indian Pines , of dimensions 145x145x200. From the data size , I am unable to gauge whether to do stratified splitting , random splitting , or plain train-test split , before ...
0
votes
0answers
332 views

How to implement one vs rest classifier in a multiclass classification problem?

I have a dataset which contains 750 data points with 8 classes in the target variable. I tried implementing simple machine learning models and also did hyperparameter tuning but they results were not ...
1
vote
1answer
139 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?

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 ...
0
votes
0answers
35 views

multi class logistic regression : $K-1$ regressors or $K$ regressors (softmax)?

I read that, in multiclass logistic regression, we have a pivot class $K$ and $K-1$ set of $\vec{w}$ weights, then, for the pivot class: \begin{eqnarray} P( C_K | \vec{x} ) &= 1- \sum_\limits{t=...
0
votes
0answers
33 views

confusion about multiclass linear classifier

I notice that there is a bit of confusion in multiclass linear classifier notation in at least 2 points: from Bishop's book and for example these slides they call the One-versus-the-rest approach (...
2
votes
0answers
71 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 ...
0
votes
0answers
6 views

How to automate the creation of multi-class target labels?

I am trying to design a modelling framework which can be completely automated. The approach involves automatic creation of features, multi-class target labels and a supervised learning model $M$. In ...
0
votes
1answer
131 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,...
2
votes
0answers
42 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 ...
0
votes
0answers
16 views

Semisupervised and Multiclass Classification

I have a dataset that includes around 400 instances (400 users' instances) with 10 features. As follows: ...
1
vote
1answer
250 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 ...
0
votes
0answers
18 views

Sentiment analysis on IMDB database and choose of metric [duplicate]

I am currently working on an extract of the IMDB available on http://ai.stanford.edu/~amaas/data/sentiment/ . Since i try to predict the label (between 1 and 10) related with each review i face a ...
0
votes
0answers
27 views

Accuracy varying considerably depending on selection of test/train set

I have a large database that is being used for a classification problem. The original total database is being partitioned 80% into sample 1 (where 80% is for training and 20% for validation) and 20% ...
1
vote
0answers
31 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. ...
0
votes
0answers
57 views

Oversampling for multi-class neural net

Does this make sense or do I have no idea what I'm doing? I want to train a model that takes a sentence and outputs a binary multi-class vector of size $K$ where each dimension is a question class. ...
1
vote
0answers
21 views

Which model to use for problem having 1000+ classes? [duplicate]

I am trying to classify text description to particular category. There are 1000 categories. How should I approach this problem? I was told to use one vs all for 1000 classes which requires 1000 ...
0
votes
0answers
37 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): ...
0
votes
0answers
26 views

Assign labels on multi label classification

I have a multi class and multi label problem: each sample can be labelled with a number of labels between 1 and n out of N. So I train N binary classifiers, so that each of those can say if the ...
0
votes
0answers
45 views

can focal loss function works for text classification problem?

I am working on a relation extraction and classification problem. The data is in the form of text files. The data is imbalanced. I want to use focal loss function to address class imbalance problem in ...
0
votes
0answers
122 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, ...
1
vote
0answers
32 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 ...
0
votes
0answers
31 views

Best method to do multiclass classification on a dataset with just 60 samples

I have a dataset with just 60 samples and for each sample I have about 45 predictors. Some of the predictors are derived from others because they represent the percentage of one predictor relative to ...
0
votes
1answer
96 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 ...
0
votes
0answers
227 views

Can I increase the accuracy of Unet by training on signal vs background (2 class) VS signal only (1 class)?

I have a Unet deep learning architecture, and it is working ok at detecting my signal, however, its accuracy is not sufficient for the purposes I am trying to use it. Let me show you an example: My ...
6
votes
1answer
111 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: ...
0
votes
1answer
395 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 ...
1
vote
1answer
213 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. ...
1
vote
0answers
170 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 ...
0
votes
0answers
28 views

Implementation of fallback class in SVM classifier

I am working on a multi-class text classification problem using SVM. I would like to add a fallback class "others" for data that doesn't belong to any of the classes. I choose features such that text ...
0
votes
1answer
874 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 ...