Questions tagged [multiclass-classification]

Multi-class classification is when you have a classification problem with multiple classes, specifically 3 or more classes. Many classifications are binary by design, therefore the additional nomenclature of multi-class classification was defined to describe algorithms capable of classifying datasets with more than 2 classes.

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23 views

Does object detection do a better job at image classification than image classification

I read in an article that object segmentation can do object detection better than object detection algorithms. I assume this is because there is more detailed information in the annotation images. I ...
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Can I turn any binary classification algorithms into multiclass algorithms using softmax and cross-entropy loss?

Softmax + cross-entropy loss for multiclass classification is used in ML algorithms such as softmax regression and (last layer of) neural networks. I wonder if this method could turn any binary ...
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Are more classes more favorable than a single combined class?

Imagine the following scenario. Train a classifier that classifies an object into one of these n+m classes: ...
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65 views

How to identify multiple lines/clusters in a single dataset

I'm currently struggling to wrap my head around how multi-linear regression could be done to find separate sets of linear models in a single data set. I can perform regression on single data set for a ...
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1answer
826 views

Transform multi-label problem to multi-class problem

What are the downsides of modelling a multi-label problem as a multi-class problem with a single classifier? Let my clarify what I mean. There at least two ways that one multi-label problem can be ...
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1answer
126 views

Which feature to use in feature selection?

Objective: Multiclass classification with supervised learning, small dataset (25h) Context: My dataset is composed of mobile network data collected with a smartphone. The labels correspond to the ...
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1answer
71 views

better confussion matrix higher LogLoss ? Is that possible>

I have tried a 2 different versions of a gbm in a multinomial classification problem. The second model results in better confusion matrix but in worse Log Loss value (at the test sample). How is that ...
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1answer
689 views

RuntimeError: Assertion `cur_target >= 0 && cur_target < n_classes' failed

I am referring this previously asked question in stack-overflow which remains unsolved till now. I am facing same problem with pytorch when I am solving ...
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Loss function for multi-class classifiction where output variable is a level i.e the various classes are dependent on each other

Let's say we are classifying Images of cat , fish and human. Classifying a cat as human is as wrong as classifying it as fish, so here the normal loss functions/ metrics like Confusion matrix is fine. ...
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2answers
551 views

Difference between LASSO penalty in neural network and just LASSO regression

I wonder whether those two have any significant differences. I think in neural network, the lasso penalty put on the loss function makes the model simpler and introduces more sparsity by ...
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2answers
226 views

Keras input for multivariate classification with LSTM using current features and previous timesteps features and y values

I am working on a multivariate binary classification problem. What I want to do is to predict a binary classification given the features at the current timestep and the data (features+real ...
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121 views

Tuning a classifier for high precision, with no regard for recall

I understand this falls under the decision making aspect, rather than the probabilistic, but for the purposes of some work I am doing, I need the classifier to have very high precision, as I can't ...
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1answer
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Is it normal for F1 scores to be lower on a binary classification task as compared to a 3-class classification task?

I am trying to understand if the F1 scores are higher for a binary classification problem than for a multiclass classification problem.
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1answer
51 views

Are there any algorithms for a classification problem involving unlimited classes, and only a few instances per class

The Scenario: A group of people must summarize specific parts of speeches they hear. They hear a new speech every day, and it's possible that multiple members of group are listening to the same speech....
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Multiclass classification of textual data

I have a problem statement in which I have to classify the text data into various classes, but the training data is very less (250-300 data points for 4 classes). I am confused about what approach to ...
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1answer
186 views

what is the difference between multilabel and multilabel-multiclass classification?

I am trying to classify news articles into their required category. However I am confused by the above(multilabel and multilabel-multiclass) terminologies. My dataset consists of 2 csv files. The ...
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2answers
735 views

How to tackle a multilabel classification problem

I am trying to build a LSTM model for a multiclass classification problem on textual data. Until now, I have only built a model when one input belongs to one of the categories. What do I do when one ...
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1answer
39 views

What is the intuition behind using LSTM for classification tasks?

LSTM is good for sequence prediction, because it can remember the previous context. What is the rationale behind using it in classification tasks ? In particular, they have used it for the following ...
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5k views

Which comes first? Multiple Imputation, Splitting into train/test, or Standardization/Normalization

I am working on a multi-class classification problem, with ~65 features and ~150K instances. 30% of features are categorical and the rest are numerical (continuous). I understand that standardization ...
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1answer
904 views

Training textblob with 16k rows of labeled data won't work (only few are working)

I've got labeled data in a csv which looks like: title,type Women Jacket A,Clothes Mens Running Shoes B,Shoes Children backpack,Bags and a script: ...
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50 views

Different result between Rapidminer and Python imblearn

I'm currently working on imbalanced classification problem. However i found different result between SMOTE in rapidminer and SMOTE in imblearn (python). rapidminer SMOTE give 15-20% improvement on ...
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1answer
52 views

How to handle overfitting in the following classification case

The confusion matrix is as below :- [[ 0 0 5 1 0 0] [ 0 0 19 14 0 0] [ 0 0 217 151 0 0] [ 0 0 84 282 0 0] [ 0 0 6 111 0 0] [ 0 0 0 10 0 0]] ...
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2answers
392 views

A robust metric in the presence of class imbalance

When evaluating the performance of a multiclass classification problem, on a highly imbalanced dataset, what is the most robust metric for this purpose? I read a paper that states: "Average ...
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186 views

Using Lift charts with multinomial classification model

I’m trying to understand the use of Lift charts with multinomial classification model in the evaluation phase. I can see only one category can be selected to use in ‘x’ axis e.g drugA . What kind of ...
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2answers
7k views

Why class weight is outperforming oversampling?

I am applying both class_weight and oversampling (SMOTE) techniques on a multiclass classification problem and getting better results when using the class_weight technique. Could someone please ...
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1answer
102 views

best approach for CNN training with multiple subcategories and one category

I need to classify pictures into 2 categories: approved and rejected. Rejected category has different type of images which are not allowed (subcategories), for example nude or gore or anime etc. What ...
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1answer
751 views

Comparing multi-class results with binary classification results

We used machine learning to discriminate the following five disease classes: Normal (N) Myocardial Infarction (MI) Coronary Artery Disease (CAD) Congestive Heart Failure (CHF). In the past, these ...
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1k views

Improve accuracy of Keras multiclass image classification with pretrained VGG16 conv_base

In the moment, I'm training my first "larger" image classification model with Keras (22 classes, 2000 train samples, 500 val samples each class). I use a pretrained model (VGG16). My current model is ...
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1answer
150 views

Any non Deep Learning python packages for sequence classification.?

Stats model or any other machine learning python packages for doing sequence classification(that can be multi class) and sequence prediction (Both next step and regression). PS : Input data will be ...
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229 views

Why the accuracy is high on both training and validation set but very low on test set?

I'm using Tensorflow to train a classifier for image recognition, the model below is built via Keras. The original data is (50000, 3072), and reduced to (50000, 100) with PCA. The explained ratio is ...
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1answer
863 views

Multiclass classification on imbalanced dataset : Accuracy or micro F1 or macro F1

I have a multiclass classification problem. Further, an instance can be assigned to exactly one class. My dataset is highly imbalanced. I know that accuracy is not a good metric to use in this case ...
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2answers
72 views

How to consume single piece of text for classification in a model?

Here's a high-level blueprint of my model - Input data:: ...
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1answer
233 views

Which model to use for multiclass audio classification?

I am working on a project wherein I want to classify Tabla taalas(patterns) and I didn't find any dataset regarding it. I am recording them myself and I've ~500 data samples recorded. What model shall ...
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1answer
2k views

Multi class Imbalanced datasets under-sampling imblearn

I have an imbalanced dataset. I am looking to under-sample. Even though, the oversampling process takes less time, the model training takes a lot of time. I have taken a look at imbalanced-learn ...
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509 views

Can McNemar's test be applied to evaluate multiclass models?

Full Disclosure: I did a semi-cross post of this question due to low traffic on Cross Validated. Once I get an answer on any of the two questions, I will link the answer back to the respective other. ...
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352 views

Adjust class weights due to class imbalance and class importance Multi class classification XGBoost

With respect to this question and the answer given by @Esmailian, Would anyone be able to let me know if Class B has a higher importance or the positive class ( i.e. it needs to have a higher ...
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104 views

Deep learning(MLP) on multiclass classification. Model learns only one class

I am new to deep learning. I have imbalanced class data. I used one hot encoding and scaling to preprocess my data. I have used adamoptimizer as optimizer function and sparse categorical crossentropy ...
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1answer
104 views

Is AUC a good metric for evaluating the performance of a multi-class classification? [closed]

Considering the definition of AUC (Area Under Curve), is that a reliable performance metric for a multi-class (30-40 classes) classification problem?
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101 views

How to pass inputs (interactively) to a model?

Let me give you a high-level design (blueprint) of my model. Input data:: ...
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1answer
226 views

Why does CV yield lower score?

My training accuracy was better than my test accuracy, hence I thought my model was over-fitted and tried Cross-validation. The model further degraded. Is that my input data need to be sanitised ...
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4answers
1k views

SGDClassifier: Online Learning/partial_fit with a previously unknown label

My training set contains about 50k entries with which I do an initial learning. On a weekly basis, ~ 5k entries are added; but the same amount "disappears" (as it is user data which has to be deleted ...
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100 views

Should images with multiple objects of the same class be used as training sample for multi-classes object detection models?

Let's say the model try to detect all the grapes on a branch of grapes. Can I use images of a grape branch with all the grapes labeled as a training sample? Will it affect the quality of the RPN ? Is ...
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1answer
144 views

Supervised multiclass classification : is ANN a good idea ? or use other classifiers?

I have a problem deciding what to use since i'm just beginning to creating predictive models. Let's say I have a training dataset with 5 or 6 features and a testing dataset. (With around 50k rows in ...
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1answer
1k views

Balancing XGboost still skews towards the majority class

I have unbalanced dataset for multiclass classification and I tried to use the class weights option in XGboost and the classifier still tends to favor the majority class. I am not sure if I need to ...
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1answer
727 views

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

I have a balanced dataset for a multiclass 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 ...
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1answer
52 views

Can this be a case of multi-class skewness?

I have been working on an email data set, and trying to predict the owner team for it. But my prediction accuracy is just 58%. I have implemented data cleansing, null value removals, duplicate removal,...
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1answer
593 views

Why do we Softmax at all?

Why take softmax at all at the final layer for multi-class classification problems? For example softmax of the vector [1, .5] Is [.621, .379] I mean if we just took the straight ratio, it'd give me [...
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2answers
1k views

Why do people use CrossEntropyLoss and not just a softmax probability as the loss?

I don't understand why one would add additional complexity to log, probabilities for the loss function of a classification Neural Network. What benefit does that have, as opposed to just using the 0-1....
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1answer
3k views

How to convert binary classifier to multiclass classifier?

I am a biggener student in Machine learning, and I want to ask if is it possible to convert a binary classifier label (y) by applying some condition on column1 to get a third situation. I.e. ...
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5k views

Products classification by name

I am a beginner with machine learning, and I'm trying to build a model to classify products by category according to the words present in the product name. My goal is to predict the category of some ...

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