Multiclass classification is a classification task in which there are more than two classes. It is also called multinomial classification.
Questions tagged [multi-class]
399 questions
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votes
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How do you calculate precision and recall for multiclass classification using confusion matrix?
I wonder how to compute precision and recall using a confusion matrix for a multi-class classification problem. Specifically, an observation can only be assigned to its most probable class / label. I would like to compute:
Precision = TP / (TP+FP)…
daiyue
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What is the difference between Multiclass and Multilabel Problem
What is the difference between a multiclass problem and a multilabel problem?
Learner
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How to compute precision/recall for multiclass-multilabel classification?
I'm wondering how to calculate precision and recall measures for multiclass multilabel classification, i.e. classification where there are more than two labels, and where each instance can have multiple labels?
Vam
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How to determine the quality of a multiclass classifier
Given
a dataset with instances $x_i$ together with $N$ classes where every instance $x_i$ belongs exactly to one class $y_i$
a multiclass classifier
After the training and testing I basically have a table with the true class $y_i$ and the…
Gerenuk
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Multilabel classification metrics on scikit
I am trying to build a multi-label classifier so as to assign topics to existing documents using scikit
I am processing my documents passing them through the TfidfVectorizer the labels through the MultiLabelBinarizer and created a…
mobius
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How to use scikit-learn's cross validation functions on multi-label classifiers
I'm testing different classifiers on a data set where there are 5 classes and each instance can belong to one or more of these classes, so I'm using scikit-learn's multi-label classifiers, specifically sklearn.multiclass.OneVsRestClassifier. Now I…
chippies
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How to handle the difference between the distribution of the test set and the training set?
I think one basic assumption of machine learning or parameter estimation is that the unseen data come from the same distribution as the training set. However, in some practical cases, the distribution of the test set will almost be different from…
Fashandge
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Best way to perform multiclass SVM
I know that the SVM is a binary classifier. I would like to extend it to multi-class SVM. Which is the best, and maybe the easiest, way to perform it?
code: in MATLAB
u=unique(TrainLabel);
N=length(u);
if(N>2)
itr=1;
…
lakshmen
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How to build a confusion matrix for a multiclass classifier?
I have a problem with 6 classes. So I build a multiclass classifier, as follows: for each class, I have one Logistic Regression classifier, using One vs. All, which means that I have 6 different classifiers.
I can report a confusion matrix for each…
Victor Leal
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How can a multiclass perceptron work?
I don't have any background in math, but I understand how the simple Perceptron works and I think I grasp the concept of a hyperplane (I imagine it geometrically as a plane in 3D space which seperates two point clouds, just as a line separates two…
grssnbchr
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Many binary classifiers vs. single multiclass classifier
What factors should be considered when determining whether to use multiple binary classifiers or a single multiclass classifier?
For example, I'm building a model that does hand gesture classification. A simple case has 4 outputs: [None, thumbs_up,…
megashigger
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Better performance using Random Forest one-Vs-All than Random Forest multiclass?
I am working on a multiclass problem with 9 possible labels, for which I have a dataset consisting of ~50.000 examples and ~200 features each. Each example can only belong to one class. The data is fairly balanced amongst the different labels.
Given…
Javi RD
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14
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Output of Scikit SVM in multiclass classification always gives same label
I am currently using Scikit learn with the following code:
clf = svm.SVC(C=1.0, tol=1e-10, cache_size=600, kernel='rbf', gamma=0.0,
class_weight='auto')
and then do fit and predict for a set of data with 7 different labels. I got a…
Tamaki Sakura
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How the probability threshold of a classifier can be adjusted in case of multiple classes?
The above is a very simple example of having a probability classifier output for a binary-class case either 0 or 1 based on some probabilities.
In addition it is straightforward how you can change the threshold. You set the threshold either higher…
George Pligoropoulos
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Predicting multiple targets or classes?
Suppose I am building a predictive model where I am trying to predict multiple events (for instance, both the roll of a die and the toss of a coin). Most algorithms that I am familiar with work with only one target, so I'm wondering if there is a…
Michael McGowan
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