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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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Data binning for interval data

I am trying to create a ML model for salary classification into 5 categories (0-90k, 90-120k, 120-180k and so on). The problem is that in my dataset almost all salary data is presented in intervals. ...
pinkkdeerr's user avatar
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Multiclass matrix loss function in scikit-learn / xgboost / lightgbm

I have data with 4 classes: $c_1, c_2, c_3, c_4$. I'd like to create a classifier which has different scaling for the loss function per class combination: $$ \begin{bmatrix} 0 & l \left( \hat{c}_{...
Avi T's user avatar
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Loss increase while accuracy also increase [duplicate]

I'm training a fairly large classification model,and I'm having the below results. ...
WillWu's user avatar
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Drum sound classification using RNN issues - help needed

I am new to the field of machine learning, even tho I have solid background in semi-related fields (am control system engineer by trade) and as a hobby project I wanted to work a bit with sound ...
APasagic's user avatar
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Multiclass PyTorch neural net is stuck predicting 1 class, even with "simple" dataset

I'm trying to predict a class of some data, and am struggling. So, to debug I created a simple test dataset, yet I am having the same issues. I've tried adding weighting, and lastly adding a column ...
Russ's user avatar
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Train-test split strategies in sensor time series

i'd like to train a supervised machine learning algorithm on my sensor data (Accelerometer XYZ). I've already segmented the data with a sliding window approach (1s window_size, 50% overlap) and ...
André S's user avatar
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Multiclass Classification for Multiple Minority Classes [closed]

I've been working on a multiclass problem (5 classes) and having some challenges on Feature Selection and Class Imbalance. I have around 1,000 rows and 2,000 features (which I also generated ...
easymoneysniper's user avatar
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Is this classifier better than a random guess?

I'm working with the SAMHSA Mental Health Client-Level Dataset. I'm trying to train classifiers to predict the disorder given the rest of the columns. There are 14 binary disorder columns (bipolar, ...
Jackson Walters's user avatar
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Can I use TimeDistributed layer for multiclass classification?

I have timeseries machine sensor data and I would like to predict when the machine fails using the sensor data. There are 4 Failure states and 1 Normal state, total of 5 classes. I am trying to solve ...
Rushabh Kheni's user avatar
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1 answer
34 views

How to deal with a heavily imbalanced test dataset?

Both my train data and test data were imbalanced. So I tried SMOTE for training. Before Smote: ...
GrGr11's user avatar
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Why is my LSTM model not predicting well when predicting labels for a new dataset?

I have a 15 timeseries datasets with 25-30 columns and is labeled by following a complex formula applied on the 25-30 columns. When training, I split the datasets as training datasets and unseen ...
Rushabh Kheni's user avatar
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IoU metric for multi class image segmentation task

My input shape is of (168,18). I create batches of size 256 and create my dataset using timeseries_from_Array_dataset. I am visualizing this 2D snapshot of a multivariate timeseries (batch size- 256, ...
Vjs's user avatar
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Are there specific properties in the area of intersections in a multiclass support vector machine one vs one or one vs rest classification problem?

For visualization what I mean in a 2D space.
Johannes's user avatar
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How to create a multi label text classification model for small dataset in production [closed]

I have a multi-label text classification dataset which is very small around 80Kb, I am only going to receive a small amount of data for training from my client. But it is expected to build a high ...
Aayesha Qureshi's user avatar
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Variable length multi class multi label problem

I have to create a model that will output a variable number of tuples of size 3 as output. The tuples have to contain some category, not a float. I've never encountered a problem as this one so I'm ...
ptushev's user avatar
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How to deal with a dataset in which categorical features have one value for specific class?

I have a multiclass problem and for the class equal to 2 in the target I have some categorical columns with just one value. For instance, is like for the observatuons with the target equal to 2, the ...
Aldla E Aoepql's user avatar
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How do I shape my output data for a time series classification problem using LSTM

I am wanting to use an LSTM for anomaly detection on a multivariate time series data. Let's say there are n rows each corresponding to a timestamp incrementing by an hour and d input features and d ...
Vjs's user avatar
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What feature selection method is best for a multi class classification problem with one-hot-encoded columns?

I am trying to solve a multi-class classification involving prediction the outcome of a football match (target variable = Win, Lose or Draw). With a dataset of 2280 rows, which is 6 seasons of ...
pastybake2002's user avatar
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Bulding Deep Learning model for multiclassification case

I am soo confused i read a lot of information in forumas and still cna't get what is wrong. my data is around 500.000 rows and 32 columns. my target variables consists of 3 classes (0, 1, 2). Hyperopt ...
Shamkhal Mammadov's user avatar
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9 views

Relationship among different classifiers of a model in multiclass problems

Suppose we are fitting a LogisticRegression model with scikit-learn, or the same model with pytorch. In multiclass problems, the strategy OneVsRest will fit a different classifier for each of the ...
CasellaJr's user avatar
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Macro-average ROC curve not looking right

I am performing a 10-fold Cross-validation on imbalance datasets with small n examples and large p attributes. I am plotting ROC curves by merging predicted probabilities obtained by testing on each k ...
Edoardo Taccaliti's user avatar
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1 answer
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Xgboost multiclass monotonic constraints

I have a problem where i have a variable price and i need to classify this price as winning/non-winning. If price grows, probability should monotonically go down. I use a monotonic constraint that ...
Jose Cle's user avatar
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0 answers
40 views

Is this the appropriate way to calculate a multiclass reliability diagram for model calibration?

I'm trying to generalize reliability diagrams [1] to a multiclass classifier and implement that using pytorch and pytorch-metrics. So far so good but I'm somewhat confused about the definition of ...
Nirro's user avatar
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1 answer
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Why is my genetic algorithm overfitting so much?

I'm only training on a fraction of the data each generation: ...
BigMistake's user avatar
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65 views

Custom loss function for multi label classification in catboost?

I have a data frame which I want to use for multi class classification problem. There are total 6 classes (say a, b, c, d, e, f). I want to improve the precision for three classes (say a, b, c) i.e. ...
SUNITA GUPTA's user avatar
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Should I need to cure the curve for the model?

I have several classification models that used for image classification. The epochs is set to 100 for both. Model A gave me accuracy 99.7 and stopped at epoch 100 but Model B gave me 99.93 but take ...
user5520049's user avatar
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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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29 views

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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1 answer
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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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1 answer
59 views

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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8 views

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
1 vote
1 answer
44 views

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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0 votes
2 answers
179 views

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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301 views

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
1 vote
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80 views

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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13 views

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 ...
jerron's user avatar
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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 ...
RXT_ Z's user avatar
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2 answers
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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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35 views

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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1 answer
38 views

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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0 answers
46 views

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
3 votes
2 answers
4k views

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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8 views

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 "...
Larsenal's user avatar
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1 vote
1 answer
701 views

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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1 vote
2 answers
173 views

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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193 views

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
2 votes
1 answer
318 views

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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