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

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Micro vs weighted F1 score

In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account? The main upside of choosing macro is that one gets a ...
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25 views

Is there any clearer term than multiclass classification?

Multiclass classification is the problem of classifying instances into one of the more than two classes. However, the prefix multi means "more than one" (as in multi-label classification: if one ...
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Evaluation of binary approach to one vs all multi-class classification

I'm working on a multi-class problem which I have redefined as a series of binary problems (i.e. a one vs all classification problem). However, each observation can belong to more than one class. For ...
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24 views

LDA scores too big

I'm trying to do dimensionality reduction with linear discriminant analysis (LDA) in MATLAB. I'm using this code to calculate the coefficients. But I'm confused whether (and when) should I center the ...
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21 views

Naive Bayes - Good for Binary Data?

I have 92 observations with 92 variables. Every observation is a binary outcome (0=no, 1=yes), indicating if that observation co-occurs with a given feature in the feature set. I have 18 classes which ...
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2answers
36 views

Online learning that “forgets” older aspects learned? (short-term memory)

I am looking for an online learning classifier that is highly adaptable and has only short-term memory. I need such a think in a object tracking system with high-dimensional feature vectors. Maybe a ...
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48 views

Binary Classification vs Multi-class Classification

In the scenario that I have a binary classification problem, and use a binary classifier to train and test my model, assuming everything else is constant, would using a multi-class classifier with 2 ...
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1answer
21 views

Quadratic error for multi-class classification

I'm trying to train a neural network to classify handwritten inputs into 10 categories, each for one digit (1,...,9,0). I represent the output of an example using a 10-dimensional vector. Digit 5, for ...
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39 views

Problem with backpropagation algorithm for Feedforward Neural Networks

The objective When trying to exercise my knowledge of Feedforward Neural Networks, I started implementing one. The result is here. The final goal is to predict some handwritten digits data I have. ...
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33 views

What is the difference between Multitask and Multiclass learning

Consider a image labeling problem, where I need to assign one or more labels to an image. The possible labels are human, moving ...
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1answer
24 views

Are the total false positives and false negatives of a large confusion matrix equal?

I have a confusion matrix which is 20x20 that is the product of a random forest classification of ~20k instances. Each of these instances was put into a specific class where rows are actual class and ...
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1answer
52 views

How to do one-vs-one classification for logistic regression?

I have a dataset with 4 clases and I want to apply logistic regression with one-vs-one classification. So, first I train for each pair of classes a logistic regression classifier (i.e. calculate the ...
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51 views

Advantages of the softmax function in feedforward multi-class neural nets over logistic activation and one vs all approach

I am wondering if there is a benefit to the softmax function over an one-vs-all sigmoid activation function approach in feedforward neural networks for multi-class classification -- except for the ...
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33 views

How do I improve the accuracy of my supervised document classification model? [closed]

Given 1000 legal judgement documents, 900 of which are labeled, my task is to predict the label for the remaining 100 documents. The labeled documents belong to 41 different categories of Law, with ...
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55 views

Vowpal Wabbit: best strategy for short text data like titles & kewords

I am using Vowpal Wabbit 7.10.0 (VW) to learn and predict categories on text data. However, my text data for each record is not like an article or another decent-size text document, but rather a ...
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1answer
23 views

Is there ever any reason to discretise continuous ground truth if doing classification?

Is there a case where discretising continuous response improves classification performance? For example: A response variable is in the range 0 to 99. There are 10 classes defined by the following ...
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139 views

How to draw plot of the values of decision function of multi class svm versus another arbitrary values?

I am trying to draw a plot of the decision function ($f(x)=sign(wx+b)$ which can be obtain by fit$decision.values in R using the svm function of e1071 package) versus another arbitrary values. From ...
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23 views

How to create and format an image dataset from scratch for machine learning?

I've only worked with ML with .csv formats. I've worked with image formats too but only premade imagesets (MNIST,etc). If I were to create an imageset from scratch, how are the class labels typically ...
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132 views

Why do one-versus-all multi class SVMs need to be calibrated?

On the wiki page for multi-class support vector machines (https://en.wikipedia.org/wiki/Support_vector_machine#Multiclass_SVM) it states that "it is important that the output functions be calibrated ...
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84 views

Balancing Per-Class Accuracy of Multiclass Classifier

Suppose I have a multi-class classifier like Naive Bayes, k-Nearest Neighbors, Decision Trees, Random Forest, etc. The classifier maps a feature vector to (let's say) 3 classes: A, B, or C. My ...
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82 views

Confusion matrix with multi-class multi-label classification

Let's say I have three possible classes {'isCold' 'isWet' 'isSolid'} and my instances can belong to one or more of these classes. Ground Truth ice = {'isCold' 'isWet' 'isSolid'} water = {'isCold' ...
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53 views

Machine learning algorithm/approach advice for a particular problem - multiclass classification?

First real meaningful dip into machine learning here for a project, and I'd like to optimize my time spent by getting the algorithms of choice nailed properly from the outset. Straight up however I'm ...
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141 views

Logistic Regression one vs all probability scores calibration

I am applying concept detection on images. For each concept I am independently applying an one-vs-all Logistic Regression instance with its own training examples. Given an image, I want, given the ...
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Measure performance of a multiples classifier that is a combination of binary support vector machines

I am comparing the performance of multiple schemes to combine binary SVMs into one multiples classifier. I was hoping to use the cross entropy, however I cannot figure out how to apply it. For ...
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104 views

Negative samples on multiclass neural network training

I want to train a deep neural network to classify images. In every implementation I have seen, multiclass training uses only the positive examples for each class. Is there any way to utilize ...
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1answer
49 views

Which one to choose and when? One-v/s-One and One-v/s-All classification for multi-class classification

In case of multi class classification task, how do we decide which among the two options viz. one-v/s-all and one-v/s-one do we choose for model building? Is there some criterion based on which we ...
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134 views

How can I derive confidence intervals from the confusion matrix for a classifier?

I have am using k-fold cross validation to generate a confusion matrix for a classifier. I need to calculate 95% confidence intervals for the number of times each class is predicted when run against a ...
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1answer
56 views

is negative log loss affected by oversampling?

I'm working on a multiclass classification problem where negative log loss is the evaluation metric. My initial train set and my static test set have similar class distribution and my validation (20% ...
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1answer
39 views

Suggestion for method/framework to use for short string classification with “complex” ouput

What I am trying to do : I have short text strings (max 128 total chars in length) which I would like to classify (or use for prediction) as belonging to a particular type of output (more on the ...
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67 views

VW multiclass classification

I am new to vw and trying to do a multiclass text classification with 18 classes. features are unigram, bigram and trigrams. Total features are around 1.4 million Total training examples 35 million ...
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529 views

Output of Scikit SVM in multiclass classification always gives same label

I am currently using Scikit learn with the following code: ...
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23 views

Is it OK to resample data in one vs all multiclass classification?

I have a multiclass classification problem and decide to use one vs all logistic regression. Since some classes are very rare (pos vs neg is like 1:100), I plan to use some balancing strategy during ...
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19 views

Classification under uncertainty in observations

I am tackling a multiclass classification problem where the values of the independent variables are not known with certainty. Instead, each observation is represented by a multivariate Gaussian pdf ...
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Do you know about SVM plait?

I need to know about how I can applied many single SVMs? because I have read about SVM plait that does this kind of classifications that is using many single SVMs to improve the classification process ...
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73 views

LibSVM totalSV for multiclass

I am performing classification of K=9 classes using linear SVM with libSVM (MATLAB warp) I am using 400 samples of data to perform the training and I'm getting: totalSV: 203 I know libSVM uses ...
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93 views

dealing with imbalanced data set in multiclass text classification

I need to build a text classification model. I have a labeled training set and my goal is to classify the new unlabeled text . My training set is composed on 6 categories, that are imbalanced. The ...
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1answer
148 views

Suggestions needed about classifier fusion

I'm working on a classification problem which involves two classifier to observe a single event. I'm providing a high level description of the problem without going into the technical details (the ...
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18 views

Multiclass target detection : N X (1 vs all) or 1 X (N vs all) ?

I am doing a multiclass classification using neural networks. say I have 10 target classes and one null (non-of-the-above-targets). is it better that I train a neural network separately for each ...
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18 views

Assign attributes / categories to users based on their activity / likes

I have a very practical classification problem for which I need some help. I have a database of users along with their activity / likes for a number of car models. I also have the category each of ...
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1answer
885 views

Multi-class logarithmic loss function per class

In a multi-classification problem, we define the logarithmic loss function $F$ in terms of the logarithmic loss function per label $F_i$ as: $$ F = -\frac{1}{N}\sum_{i}^{N}\sum_{j}^{M}y_{ij} \cdot ...
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Walking recognition

I have walking samples from 20 different people. My aim is to detect which walking samples are from which person. I'm trying to achieve this by extracting "walking cycles" from each person's dataset ...
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643 views

Logistic regression with multi-class features in R

I'm working with a data set like the following: X = ...
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1answer
333 views

Softmax regression or $K$ binary logistic regression

For a multi-class classification problem, we can use $K$ binary logistic classifiers, or one softmax regression classifier, so how to make the choice between the two? IMHO, the $K$ binary logistic ...
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369 views

What is the difference between a multi-label and a multi-class classification?

What is the difference between multi-label classification and multiclass classfication. Speficially, what is the difference between a label and a class? Please provide a clear example. "Multiclass ...
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1k views

How to get confidence on classification predictions with multi-class Vowpal Wabbit

I have a classification problem in which I'm using the --ect option for the multi-class algorithm. The output of the classifier is something as follows: ...
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103 views

What should I use - Multi label classification or Multi class classification? [duplicate]

In my dataset, I have 2 labels, positive and negative. Most samples belong to only one class, either positive or negative. A small fraction of samples take both labels i.e. both positive and negative. ...
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2answers
98 views

Can a nuisance multi-class classifier do better than binary classifier?

This is rather a theoretical question in order to save the trouble in trying to do empirical testing and is part of a bet, so I hope I am right... Say there are M classes in the data BUT you want to ...
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1answer
359 views

What is the difference between accuracy and agreement?

According to Manning et al. (p. 155) accuracy is the sum of the diagonal in the confusion matrix divided by the sum of all items. On the other hand, following Artstein and Poesio (p . 558) precisely ...
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56 views

Limit multiclassification SVM - ANN

I have some questions on the limits of SVM and ANN for multiclass problem. I know about "one vs all" and "all vs all" strategies but I only want to know the limit of a unique SVM and ANN. Is there a ...
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156 views

Linear statistical model with two-class variables

Suppose I have a set of (discrete) variables, say $X_1,\dots,X_n$. Each $i$ belongs to either class A or class B. When it belongs to A the contribution is $Y_{A,i}f(X_i)$, and when it belongs to B the ...