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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How to solve classification problem that we should cluster elements, with Multinomial classification from CS229?

I just learned about Multinomial classification (CS229 Lecture note (What I learned is on page 24)) and I attempted to solve a problem that Obesity classification from Kaggle. Kaggle Link I tried to ...
Gosu Choi's user avatar
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Test accuracy is very low, compare to Trian and validation accuracy for image classification for 400 class

I am working on image classification with 400 class , during training , I am getting good training and validation accuracy , but test accuracy is approximate 0-1% .My input image is 1 scale , with ...
NeelPatwa's user avatar
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Numerical issue with softmax regression implementation on MNIST

I'm having numpy numerical issues with my implementation of softmax regression/multiclass logistic regression on the MNIST dataset. The numpy exp and log numerical issue goes away when I divide the x ...
KaizerBox's user avatar
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Error while using saved logistic regression model on scoring vector data -The columns of A don't match the number of elements of x. A: 6011, x: 232964

0 I'm getting error while using saved logistic regression model on scoring vector data. SparkException: [FAILED_EXECUTE_UDF] Failed to execute user defined function (ProbabilisticClassificationModel$$...
Kunal Sinha's user avatar
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Why is the sprase categorical accuracy decreasing every epoch and predictions are always NaN?

Problem Summary My model is built and compiled properly but gets the NaN validation loss on all epochs. The training set accuracy is also infinitesimally small and keeps decreasing. I couldn't find a ...
Joachim Rives's user avatar
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3D Design file labelling and classification for manufacturing

I have ~1 million 3D design (.STP and/or .OBJ) files of various parts for medical devices, aerospace, automotive or defense systems. I'd like to label them based on appropriate manufacturing methods ...
rootcage's user avatar
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When is Recall@k useful for a classifier with softmax-like output?

If a 3-class classifier returns a length-3 vector of probabilities, e.g. [0.1, 0.85, 0.05] for classes A, B, and C respectively (strongly indicating B), does it ...
Alex Shroyer's user avatar
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How do design a 2 class+noise classifier system

I need to train a 2 class classifier for a 30 x 6 frame. In the dataset, there exists data for class A and Class B, but there is a lot of junk data as well which particularly does not classify into ...
Fr_nkenstien's user avatar
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How in the heck should I tackle this classification problem? I'm not even sure if it's classification or regression

So, I'm currently a third year student in electrical engineering and I'm currently enrolled in a Mathematical Modelling and Machine Learning class and we're currently tasked to classify or use ...
the big's user avatar
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How to improve accuracy on a single class out of 3 classes in model

I am training a classification model with 3 classes using a deep neural network. The classes have been resampled and balanced. I have around 600000 samples... equally distributed. The dataset is also ...
Fr_nkenstien's user avatar
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How do I get SAM to perform multi-class classification?

I want to use the Segment Anything Model(SAM) to perform multi-class segmentation on satellite images. When I tried to apply it, it ended up giving single-class outputs. Moreover, upon applying a ...
Ipshita Ahmed Moon's user avatar
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Why do I keep on getting ResourceExhaustedError while training on video data using CONV3D on tensorflow?

I'm encountering a memory allocation problem while training a deep learning model on my computer, which has a Core i9 10th Gen CPU, 64 GB of RAM, and an NVIDIA GTX 1660 Super with 6GB of VRAM. Despite ...
Ali Subhan's user avatar
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Loss function for classifcation rewarding closer guess?

The default loss function in multi class classification is cross_entropy, which treats all wrong guesses equally. If the distance between buckets are meaningful, for example, given the real bucket is ...
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Is a csv file to store image path and class neccessary for image classification?

I just get my hand-on a basic deep-learning project. I am working on multi-class image classification project with e-commerce dataset. I am not sure whether by storing training images in sub-folder ...
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what is a random prediction for class imbalanced data? How can I check if my model is predicting randomly?

Say if you have a balanced dataset, with two classes, if the classification model that we’re training doesn’t learn anything ( suppose the data is random ), the model’s output would be 50% first class ...
ZEINab Sadeghian's user avatar
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Metrics to use for multiclass classification

I was asked in an interview that I have imbalanced dataset of multiclass categories. For example out of 1000 data points 700 fall in cat1 , 75 in cat2, 90 in cat3 , 50 in cat4, 50 in cat6 , 35 in cat7....
Payal Bhatia's user avatar
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How can I solve this kind of problem about predicting the sequence of once in life events?

So let's imagine I have a dataset of children. For each of them a have a bunch of characteristics (generation, gender, race, class, urban/rural, religion, bmi, number of siblings etc..) and plus the ...
Floralys's user avatar
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Classification errors on 'bert-base-uncased' text classifier

Disclaimer : This is a long question, please be patient. Thanks in advance I am using bert-base-uncased for text-classification. I have 11 classes, and the classification is happening alright for most ...
Vinay Varahabhotla's user avatar
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How to read confusion matrix from multiclass dataset?

I have a dataset with multi class for classification. After train and test, tried to plot with confusion matrix. And I found it really different with dataset with simple label true false or yes no. So ...
yozawiratama's user avatar
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What are the implications of framing a classification problem against classes conceived as DAG vs DAG-SS?

Imagine a problem where one needs to characterize documents within a hierarchy of classes. I'll use the simple animal example where a document may fit "dog" or "cat" or "...
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Keras outputting integers rather than class names / labels?

I've created a ANN using Keras to predict what class a specimin belongs in based on other variables. I used label encoding to turn these classes into integers (Dogs,cats,horse,etc) to use in the ANN. ...
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Treating a Multi Task Problem as Single Task

In my model, the input is textual data. I have 5 targets, and each can take values from 0 to 5 (categorical values), which means that I am dealing with a multi-task problem and I need 5 heads for 5 ...
mansoor sh's user avatar
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I used SMOTE-ENN to balance my dataset and it improved the performance metrics, but how can I be sure it's not overfitting?

The models were evaluated using 10-fold cross validation. foldCount = StratifiedKFold(10, shuffle=True, random_state=1) The models in question are XGBoost. ...
Tariq's user avatar
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Class Imbalance in Dataset of Images

When dealing with an imbalanced dataset, I have been taught to oversample on only the train samples and not the entire dataset to avoid overfitting, however this was for structured text based data in ...
osmans's user avatar
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Weighting and loss function for multi-dimensional output on ECG neural network in Tensorflow

I am working on a DNN that is training on ecg data with a shape of [None,1,2500] and output shape of [None,12,19] where 19 is a ...
ekg-display's user avatar
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Multiple classes present in one-hot encoding

When dealing with classification for multiple classes present in the same sample, can the output layer have the form of one-hot encoding, but instead of only one hot, have multiple? That is, in case ...
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Is there a way to use CNN to separate/cluster the images into N clusters without online learning or only very mild online learning?

There are lots of examples to use CNN as classifier to separate images into known classes. There also lots of examples to use CNN as encoder and generate embedding to check the similarity of objects. ...
Wang's user avatar
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What else can I do to help my model my classification task?

I have a classification task that I'm currently getting really low accuracy metrics on (my highest accuracy score is about 20%). So far I've run 5 models: quadratic disc analysis, logistic regression, ...
FLAN - Legacy's user avatar
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What to do if my dataset have only One instance for class in classification?

I am working on a benchmark dataset for text classification. The dataset has about 300 classes, and approximately 50 of these classes have a single instance. In a paper that used fine-tuning BERT, the ...
mandana hosseini's user avatar
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How to explain relative difference between macro-AUC and macro-F1 in a multiclass classification problem?

I recently published a paper in which the result of a supervised model is the following. All the metrics are macro-averaged. I have been asked to comment on the gap between the AUC and the other ...
Eric Yamga's user avatar
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1 answer
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Movement in cohorts

I am working on a user sales data which gets updated week over week. Based on the sales done in each week, the user is categorized in segment A, B or C. This means size of each segment could change ...
Sham's user avatar
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Unable to get explainability for sklearn Random Forest classifier using Shapash

I'm using SmartExplainer of shapash 1.6.0. I have 30 input features out of which 25 are categorical. I have preprocessing transformer object for the same. The code snippet is as follows ...
priyank chopra's user avatar
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Getting Error: TypeError: cross_entropy_loss(): argument 'target' (position 2) must be Tensor, not tuple

I am working on a CNN multi-class classification of different concentrations (10uM, 30uM, etc.) I create my dataset to include the images as the features and the concentrations as labels. Note that ...
Zelreedy's user avatar
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2 answers
164 views

Data Preparation for next word prediction

In most places, I have seen that when preparing the training data and label for next-word prediction from the corpus one uses a fixed window size say of length 4, and then scans the subsequences of ...
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Multi-label classification inference

I am working on a multi-label classification with transformers. I want to assign tags to input text. First, I have trained a model multiclass and with the pipeline function I can retrieve all possible ...
chancar's user avatar
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What loss function to use for predicting discrete output sequence given a discrete input sequence?

I am working on sequence-to-sequence tasks where the input is an n-length sequence of discrete values from a finite set S (say ...
NotNotLogic's user avatar
2 votes
2 answers
1k views

How to do train-test split for multi-class classification

I am performing multi-class classification problem of different concentrations of Acetaminophen in a specified dataset. My data is in the form of images and I am using CNN. I have compiled all the ...
Zelreedy's user avatar
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520 views

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'...
AngelMarcos's user avatar
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How to deal with ambiguous classification outputs that exceed the specified threshold but are too close together?

I have a simple classification setup (intent classification). Once an input is received it's parsed using Multinomial Logistic Regression and then a score is predicted for each class. I pick the ...
Metrician's user avatar
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What statistical model suits for this problem?

I have a dataset with 6 target variables and the target variables are Boolean. The requirement is to use logistic regression to build the model. Which ML approach can be used in this situation? Will ...
Miuni Nihara's user avatar
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Do I need to use always the same "Test" dataset to compare between different models?

I have two datasources A and B, and I want to check how several methods can affect the accuracy of my multi class models: If I use cross-validation with validate dataset to obtain the best hyper ...
Just_4n0th3r_Pr0gr4mm3r's user avatar
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DecisionTreeClassifier cannot take one-hot encoded classes?

I got ValueError: Found array with dim 3. None expected <= 2. I dont know which array has dim 3? DecisionTreeClassifier cannot take one-hot encoded classes? But ...
user900476's user avatar
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WARNING:tensorflow:Your input ran out of data; interrupting training Error

Due to VRAM capacity limitations, I cannot fit the whole training and validation data into the GPU memory. Instead of cutting some of the data out, I decided to use TF.dataset object to create the ...
Mohammed Nafie's user avatar
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How to get the top feature contributors for the differnt classes in the classifiction model?

In classification model , we build models with binary/multi class responses. Is there way to get the top features contributing positively,negatively to each of the classes.( i.e top features helping ...
Scope's user avatar
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error useing soft max gives outputs greater than 1

I am using Hugging Face AutoModelForSequenceClassification, model is roberta, using it for text classification. There are 3 classes. The output is: ...
prajwal rao's user avatar
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Multi-class classification model unable to return desired outcome

I have a scenario of multi-class dataset with around 10 distinct classes of target. There are 3 categorical features each with multiple labels. If we check the data, each unique combination of feature ...
soumalya saha's user avatar
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LSTM model is producing really bad results for multiclass text classification for imbalanced small dataset

I am training a LSTM model on my current dataset to predict the multiclass categories - there are 18 mutually exclusive categories and the dataset has ...
Django0602's user avatar
1 vote
1 answer
57 views

If I'm comparing performance between two different datasets should sample and class size be uniform?

If I'm comparing performance between classification models on two different datasets should the number of samples per class, the number of classes, and features per sample be the relatively the same ...
StrWrs_Nerd's user avatar
1 vote
1 answer
30 views

Predicting many classes, is it a known solution to build n-group classifiers?

Imagine you want to predict 2048 classes. Instead of asking one model to predict all of them at once, is it a known type of solution to have a model predict which cluster or group of classes an input ...
Jonathan Allen Grant's user avatar
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Get dependant probabilities in multiclassification

After training my CatBoostClassifier model I call get_proba function which returns me list of probabilities. The problem starts from an another point... I transfer that data into dataframe then to ...
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