Stack Exchange Network

Stack Exchange network consists of 175 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

Questions tagged [multi-class]

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

0
votes
0answers
7 views

How to calculate precision-recall curve for multiple binary classifier for multiple classes

I am using autoencoder based multiple binary classifier for text regeneration each trained on data related to multiple classes. In other words, each classifier is trained to classify only one class. I ...
0
votes
0answers
7 views

Multiclass classification with a balanced dataset and one high-priority label

I have a balanced dataset for a multi-class classification problem with one high-priority label (this ought to be classified properly at all costs). How do I go about creating a workflow for this ...
0
votes
0answers
25 views

Is Multi-output Multi-Label classification possible for this merging problem?

I have programmed a game called cell wars where cells can capture other cells via merging. The image below shows the same board before merging (top) and after merging (below). Basically, overlapping ...
0
votes
0answers
17 views

Identifying Misclassifications

Let's say there's a process that takes in an observation X and assigns it to one of 3 classes: A, B, or C. It's believed that this process routinely assigns observations to class A when they should'...
0
votes
0answers
9 views

How to ensemble predictions from image classifier and text classifier?

I am doing multiclass classification based on images and text. I have predictions from both image classification and text. I am not sure how to combine them. Should I use probabilities as a feature to ...
0
votes
0answers
14 views

Machine Learning, which kind of classification should i use?

So im trying to make a ML classifier model to my data. My data has many X(variables [texts, integers, binaries etc.]) and 5 output(Y) information. In short, lets say i have 5 different places to put ...
0
votes
0answers
18 views

How to choose metrics for evaluating classification results?

Recently we have developed a python library named PyCM specialized for analyzing multi-class confusion matrices. A parameter recommender system has been added in version 1.9 of this module in order ...
0
votes
0answers
17 views

Intuition Behind One Vs. All Linear Least Squares Classification

I understand that in the one vs. all classification approach, we form $k$ discriminants, one for each of the $k$ classes and that $(w_k - w_j)^Tx + (b_k - b_j) = 0$ is the hyperplane decision boundary ...
0
votes
1answer
35 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 ...
2
votes
1answer
30 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 ...
0
votes
0answers
33 views

SMOTE and ROSE methods in CARET (R) do not work for balancing a multi-class dataset

SMOTE and ROSE methods in CARET (R) do not work for balancing a multi-class data set. Specifically, ROSE throws an error telling that it needs two levels. It means that it does not work for multi-...
0
votes
2answers
31 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 ...
0
votes
0answers
8 views

Is it possible to have a constent accuracy for my tensorflow network whatever is the iterations?

I am runing my tf NN composed by one input, one hidden and one output layers the number of hidden nodes if the half of total features number I have got the next table considering different learning ...
0
votes
0answers
9 views

Hierarchical vs multi-class, when to use what?

I am looking for suggestions from machine learning research perspectives about using hierarchical classifier vs multi-class classifier. For example, if I have to classify 3 classes, let's say, 2 ...
0
votes
1answer
24 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 ...
1
vote
1answer
91 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
24 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
44 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
16 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
109 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
147 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
16 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
19 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
181 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
30 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
23 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
81 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
18 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
71 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 ...
3
votes
1answer
164 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
153 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
50 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
319 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
493 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
203 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
59 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
68 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
89 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
7 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
138 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
54 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
18 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
369 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
19 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
31 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
41 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
75 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 ...