All Questions
Tagged with classification multi-class
263 questions
1
vote
1
answer
27
views
Reason for softmax approximation in Ian Goodfellow's deep learning book
In section 6.2.2.2 (equation 6.31) they state:
Overall, unregularized maximum likelihood will drive the model to learn parameters that drive the softmax to predict the fraction of counts of each ...
1
vote
0
answers
18
views
How to train a neural network to identify multiple features in one image, where the order of predicted features doesn't matter
I recently created a toy dataset for myself, which I call "multi-color MNIST", where multiple digits with different colors appear on a single RGB image. See the image I attached. I am using ...
0
votes
3
answers
139
views
False Negative vs False Positive for Multiclass classification
Suppose I have three classes 1,2,3.
And there's evaluation like below, where second element is false prediction where model predict class 3 while ground truth is 2.
...
0
votes
0
answers
47
views
Applying PCA Before Training Multiple SVM Binary Classifiers To Reduce Data
I am working on a project which has a goal to determine if a new sample is part of Class A or Class A'. I need multiple of those classifiers. I will have an SVM to classify between:
ClassA - ClassA' ...
0
votes
0
answers
27
views
Theoretical support for sample size exponential increase with dimensionality in nearest neighbour multi-class classification
In multi-class classification using nearest neighbour, I believe that as the dimension of the space increases, we need exponentially more samples to keep the classification error under a certain ...
3
votes
3
answers
359
views
One class never gets predicted, regardless of the model
I'm working on a classification problem from a dataset containing three classes, with proportions {"0":0.43, "1":0.25, "2":0.30}.
...
0
votes
0
answers
22
views
How to compare if multi-class outputs are different?
I am testing different multi-class (16 classes) classification models (ANN, DNN, DL, and so on) and the overall accuracy varies from 0.75 to 0.92. Despite that 0.92 is greater than 0.75, is there a ...
0
votes
1
answer
248
views
Making a multiclass classification problem binary during data preprocessing vs using a multiclass classifier
Sometimes you have a problem that presents as a multiclass problem in your data, but you only care about the result of a binary classification. E.g. you have a manufacturing process which can result ...
1
vote
1
answer
80
views
Clustered data and multiclass classification with GPBoost
Is it possible to do multiclass classification using GPBoost?
For example when we have 3 or more classes (e.g. specie A/ specie B/ specie C) from a clustered data set (e.g. several measurements over ...
2
votes
1
answer
180
views
XGBoost Calibration for weighted loss function
I am currently using XGBoost (in R) to perform multiclass classification. I am using merror=eval_metric and my objective is <...
4
votes
4
answers
749
views
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 ...
2
votes
2
answers
105
views
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 ...
0
votes
0
answers
91
views
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 "...
0
votes
1
answer
13
views
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 ...
2
votes
0
answers
59
views
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 ...
1
vote
1
answer
1k
views
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 ...
1
vote
1
answer
106
views
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....
2
votes
0
answers
430
views
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 ...
1
vote
1
answer
48
views
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 ...
2
votes
1
answer
431
views
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 $\...
4
votes
1
answer
3k
views
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)...
1
vote
1
answer
253
views
How to handle with long-tail classification
I have a long tailed distribution with many classes,
and the num of samples per class is
...
1
vote
0
answers
45
views
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?
1
vote
1
answer
101
views
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 ...
1
vote
0
answers
150
views
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 ...
4
votes
2
answers
286
views
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 ...
1
vote
1
answer
34
views
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 ...
1
vote
0
answers
37
views
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 ...
1
vote
1
answer
92
views
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 ...
1
vote
1
answer
37
views
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),...
1
vote
1
answer
156
views
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 ...
2
votes
1
answer
690
views
Optimize classification rule in multinomial logistic regression
We know that in the case of logistic regression, a classification threshold p=0.5 is generally not an optimal choice when seeking to optimise sensitivity and specificity. This is generally due to the ...
0
votes
1
answer
456
views
Low classification accuracy
I want to do a multi class classification with 6 classes. Whole dataset has 12750 and 56 features samples, so every class has 2125 samples. Before prediction I reduces amount of outliers by ...
2
votes
1
answer
2k
views
How to use time-series observations on multi-class classification problem?
I have a multi-class classification problem with time-series features. You can find an example series below. It shows the same series over time for different classes (actually, each line represents ...
3
votes
2
answers
2k
views
Difference between ROC-AUC and Multiclass AUC (MAUC)
I am trying to understand the interpretation of these metrics in a multiclass scenario: ROC-AUC and MAUC. Scikit-learn provides ...
3
votes
1
answer
918
views
How to predict both category and sub category in machine learning classification?
There are 4 actions available. Each action has its own varying number of categories.
The target is to predict an action along with the category of action, given input data.
Assume actions are a,b,c,d
...
4
votes
2
answers
875
views
Machine learning for causal inference
I have a multiclass classification problem where the target variable is actually different categories of causes, and the dataset is observational. I know of causal inference, and I would like to learn ...
4
votes
1
answer
167
views
How the SVM algorithm works with one label in range?
I have a dataset where the features are configurations (numeric values) that describe the situation and the label (only one) is the ranking of the situation (natural value between $[1,5]$). If label ...
0
votes
0
answers
322
views
Can I use Pearson's correlation coefficient or Spearman's rank correlation coefficient as metrics for multi-class time series classification?
I am doing a 3-class time series classification problem, where classes are 0,1 and 2. For example, the test set is ...
4
votes
3
answers
1k
views
Effects of class imbalance on neural network weights
My question is about unbalanced classes problem in case of a classifier neural network for natural language processing (in particular, a neural network with LSTM).
I want to train a neural network to ...
2
votes
1
answer
620
views
How to fully evaluate a multiclass classification problem?
When you have a multiclass classification problem, what is the right way to evaluate it's performance?
What I usually do is to display the confusion matrix and the ...
0
votes
1
answer
474
views
How to practically calculate the accuracy of each class in muliclass classification problem?
I have the following confusion matrix:
...
0
votes
0
answers
105
views
Should I scale my data before a Cartesian-to-spherical conversion?
If I have three features, should I scale them before converting them to a spherical coordinate system?
I have been working on a ternary classification problem. My data is high-dimensional, so I've ...
0
votes
0
answers
1k
views
under sampling a multi-label dataset
I have a multi-label dataset, whose label distribution looks something like this, with label on x-axis and number of rows it occurs in the dataset in y-axis.
...
2
votes
1
answer
163
views
Looking for multilclass classifier that can handle repeated measures
I am looking for a multiclass classifier that can handle repeated measures. Specifically, each of my subjects appears multiple times with the same number of n classes. Now I would like to fit a ...
5
votes
1
answer
1k
views
How to draw ROC curve for a multi-class dataset?
I have a multi-class confusion matrix as below and would like to draw its associated ROC curve for one of its classes (e.g. class 1).
I know the "one-VS-all others" theory should be used in ...
1
vote
1
answer
402
views
Can in theory a multiclass neural network classifier be seen as multiple binary neural network classifiers? [closed]
I would like to know more about the theoretical implications of such a statement.
0
votes
0
answers
339
views
Given a multiclass classifier, calculate one threshold per class to maximize recall under precision constraint
Given a classifier $f$, $N$ possible classes, and an input $x$, $f$ produces a class from $[1,..., N]$ and its matching confidence $[0,...,100]$.
Then I run $f$ on a large set of examples $X$, and I ...
0
votes
0
answers
17
views
How to get multiple outputs using classification techniques?
I want to predict roles based on technical skills column.I have column technical skills for ...
0
votes
0
answers
46
views
Which model to use for multiple outputs in classification problem
I want to predict roles based on name, experience, soft skills, technical skills . Based on all these variables I want to ...