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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Should we increase the number of samples when adding more classes?
Assume we are solving a $k$-class classification problem, $k \geq 2$, and we have a trained classifier $\phi$ from a family of generative or discriminative classifiers $\Phi$
minimizing an objective $\...
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How to encode multiclass target variable?
I have a ML project for classifying news articles. In my dataset I have a target variable called "category", which represents type of the article, ("IT", "Science & Tech&...
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Multiclass Classification using Binary Representation and Sigmoid Activation in Neural Network
I am currently working on a multiclass classification problem where I have categorical variables that I've encoded using binary representations as follows:
...
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Using regression where the ultimate goal is classification
Some background information about what I am trying to model before asking my question: Long periods of hot temperatures and dry conditions (heatwaves) puts pressure on the components in the power ...
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Ideal scoring rules for multitask classification?
I am seeking advice for the best way to score a multi-output/multitask classification model's output.
Problem setup
A simplified version of the model is as follows:
Training data have F features, say ...
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Metrics for multiclass classification
Background
Consider a clustering problem where a dataset of measurements $Z\triangleq\{z_i\}_{i=1}^m$ must be partioned in $n$ clusters, where $n$ is unknown and must be estimated.
Here the term "...
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Hierarchical labelling for independent variable in training data
I have data where the objective is to use supervised learning to predict 4 different outcomes.
Say the classes are 1, 2, 3, 4. Though discrete, they are also hierarchical, where class 2 is of an ...
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Multi-class classification, KBestFeatures, different scores best for different labels - intelligent way to approach?
So I have a dataset with about 6x features as I have samples, which are balanced across 8 classes. I set out to figure out which features are important for each label. I've been approaching this using ...
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Multilabel classification problem
I have a problem statement where I have two dataset one labeled where a data point can belong to only one class say class1 or class2 and there's another unlabeled dataset. Now for unlabeled dataset I ...
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Multilabel Classification Task using SVM
I want to classify diabetic retinopathy grades (normal, mild, moderate, severe, PDR) using SVM.
But the problem is i don't know which type of svm should i use, because i extract three lession features ...
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find the optimal threshold for each class in model.predict (multiclass segmentation)
I have a unet segmentation model, which outputs 5 classes, I would like to find the optimal threshold value for each class using the precision-recall curve:
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Customized F1-Score for multi-class classification
Let's consider a multi-class classification problem with 4 classes: 0, 1, 2, and 3
F1-Score 'macro'-averaged is calculated like that:
...
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Repeating Target Values in output [closed]
I have created a multiclass predictive model, however, the target values are repeating. Why one of the target value is repeating and how can it removed?
The code for this is as follows:
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Huge overfit on prediction model -due to data with low predictive power or can this be fixed? (Python)
I am not used to working with machine learning models, and are currently sitting with an issue i hope you can help me with.
I am sitting with a multi classification problem, where i try to predict ...
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Is there a multi-class classification model which can incorporate partly known conditional probabilities of the targets?
I am faced with a classification problem where I wish to predict 2 binary variables, say x and y. x and y are dependent in the sense that one conditional probability vanishes: P(y=1 | x=0) = 0. I am ...
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How to predict multi-class multi-level category data in machine learning classification?
I have a data that it is include multi-level categories. I need to classification it by multi-label and multi-level classification model. may please tell me how can I do it by machine learning or ...
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Very balanced dataset and a multiclass classification problem, no context behind the inputs. Which evaluation metric to use?
I have constructed a simple neural network model, for a classification problem, with 10 target classes where an input (with some number of features) is to be classified to only one of the 10 classes.
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How to maximize Precision for each class in target instead of for the whole multiclass classification model using Hyperopt in Python?
I try to build multiclass classification Machine Learning model in Python. I use Hyperopt to tune my hyperparameters as below:
1. Define Parameter Space for Optimization
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How to compare labels from clustering analysis and original ones?
I was asked to run a clustering analysis to assess the validity of labels for a manually labelled dataset.
I can simply save the actual labels (4 classes: 0, 1, 2, 3) and run clustering analysis (let'...
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Multi-Label Classification where each label is a Multi-class problem
Problem:
Currently, I have 15 classification models(multi-class + binary). Training and Maintaining 15 models take a huge time and cost. Also, I need to inference 15 models for every input. So I ...
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Calculating 95% confidence interval for multi-class predictions
I have a multi-class classification model that predicts
the following probabilities for 4 classes in 3 test cases:
...
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R SVM classification with kernlab and user-defined kernel
I am trying to perform multi-class classification using SVMs (C-SVC). I am using the ksvm function from the kernlab package in R....
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How to cluster and visualise vectors of which the components are class indices?
Let's say I have a dataset $\boldsymbol{\mathcal{X}}$ of $N$ samples wherein each sample $\boldsymbol{x}^{(i)}\in \mathcal{X}$, $i \in {1 \ldots N}$, is described by a set of $D$ features, such that $\...
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Does scikit-learn support plotting calibration curve for multiclass classifier?
I have trained a multi class classifier and calibrated the classified using scikit-learn library's CalibratedClassifierCV class. To check how well the probabilities are calibrated, I tried plotting ...
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Incorporate known class likelihood (proportions, ratios, etc..) in the classification output
I'm working on the multi-class prediction problem, with 6 output classes. These represent different types of land cover. The classification model is pixel-based and I have extracted different ...
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R SVM Observation weights
I am trying to perform multiclass classification using an SVM classifier in R (I am using the svm function from the e1071 ...
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Can XGBoost do classification based on linear combinations?
Suppose we have a data set $\mathcal{D}$ consisting of $n_C$ continuous features $\boldsymbol{X}_1, \boldsymbol{X}_2, \dots, \boldsymbol{X}_{n_C}$ and we wish to target a discrete variable $\...
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LightGBM interpretation of monotonic constraints in multiclass classification
When using LightGBM in classification problems it is possible to use monotonic constraints. In binary classification problems the interpretation is straightforward: "The probability of class (say)...
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How to handle with long-tail classification
I have a long tailed distribution with many classes,
and the num of samples per class is
...
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How to solve a multi-class and multi-label classification?
im trying to classify a picture of columns with 4 squares that need to be marked and 26 question that represent a Multi Choice Question exam
each question labeled like this:
[],[],[],[X] -> 1, [X],[...
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3 classes imbalanced and hierarchical classification
I need to classift a dataset with 3 classes:
A - 85% of the data
B - 10% of the data
C - 5% of the data
Where C is a subset of B.
What should be the best way to approach it?
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How to determine the ROC AUC score in sklearn for multi-class classification problems
In https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html, the multi-class ROC AUC score can be computed by multi_class='ovo' or ...
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How do I know which class has been difficult to learn for my multi-class model?
For a multi-class model, there are always chances that the model is learning one class's features more than the other. But how do I find which class has been weakly learned? Please help.
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Linear Classifiers -- Single Linear Layer with k Neurons vs 'one vs rest' (k Linear Layers with 1 Neuron)
When using a linear classifier for a k-class classification problem, is there actually any difference of using
a single linear layer with ...
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How to assess calibration of probability distribution for a multiclass model?
I have a multiclass classifier (boosting model), and my goal is to have a good approximation of the actual distribution to the classes given my feature values.
I.e. suppose I have features $X$, and ...
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Possible overfitting with biometric signals
I am working on a machine learning algorithm that can predict three types of social anxiety state: baseline, anticipation anxiety and reactive anxiety.
The features taken into consideration are: "...
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How to convert continuous into categorical such that class imbalance algorithms work smoothly
I was trying to use : (for addressing class imbalance in classification problems)
https://imbalanced-learn.org/dev/references/generated/imblearn.combine.SMOTETomek.html#imblearn.combine.SMOTETomek....
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Considering class distances in multiclass classification
I have a dataset with $12$ classes, $C_i, i=0,\dots,11$. I would like to perform multiclass classification by engineering the learning process so that it takes into account that some classes are ...
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Multiclass ROC curve about one vs one
I am learning ROC about multiclass problem.
I read this article https://towardsdatascience.com/multiclass-classification-evaluation-with-roc-curves-and-roc-auc-294fd4617e3a .
I am confused about ovo ...
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Prediction of 'other' class
I'm training a MLP classifier with a softmax output that outputs 4 classes.
For my particular application I'd like the classifier to output a fifth 'other' class when the input don't belong to any of ...
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Why does SKLearn's Logistic Regression model have the same coefficients as my own model for 1 class but have different coefficients for other classes
I am currently implementing logistic regression from scratch and I'm comparing my model with SKLearn's logistic regression. Since this is just an exercise, I decided to use toy data, specifically ...
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What is the benefit from going from unordered to oredered data?
Let us assume that we have naturally ordered data that we want to classify. Then we can use ordinal regression/classification methods. Yet we can treat those as unordered and use multiclass ...
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Classifying dataset with different number of features
I have a dataset like below:
samplename position reference alternative
S1 201 C T
S1 3567 A G
S1 760 T C
S2 356 C T
S2 6787 T C
These data belongs to patients and ...
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How do i design my CNN so that i picks up on details like a logo [duplicate]
i'm quite new to machine learning, so i hope i can get som help on here.
I try to classify pictures of soda-cans and bottles with size 299x299. So based on the shape of the object itself, my networks ...
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Ways to detect noise in multi-class classification training data using text embeddings (BERT)
So I have a dataset with a column of text and and labels (5 different labels) associated with it. The labels describe the potential answer to the type of question being asked in the text column. For ...
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Train a neural network model that works even if some input features are missing
Background
I am designing a NN model for a multi-class classification problem. The model takes two sets of features, F1 and F2, for making a prediction. However, F2 might be missing in production, but ...
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How to calculate the total number of inputs in CNN?
I search this kind of question for a while and I find many discussions involve on counting the number of parameters of a Convolutional Neural Network, but not on the inputs. Using the Fashion MNIST ...
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Should I train my classifier with examples that are outside my classes of interest? And should I create an "others" class to handle them?
This is a 2 part question regarding a multi-class classifier based on a neural network that is expected to predict whether the input image has a cat or a dog. If shown something different (like a man),...
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CNN for multi-class classification with occasional multi-labels
I have about 10 classes, on which I train a CNN with a softmax output layer using one-hot encoding and categorical cross-entropy loss.
The problem is that two pairs of these of these classes (let's ...
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Are Type I and Type II errors in multiclass problem appear to be the same?
As far as I know from binary classification
FP error is a type 1 error
FN error is a type 2 error
I have this confusion matrix generated:
And here I found how to read this confusion matrix:
As you ...
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