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Questions tagged [classification]

An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

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Weird behaviour when using RobERTA for text classification

I have a dataset with around 70 classes and the dataset is largely balanced ~150 samples per class. I am finetuning RoBERTA-base for 4 epochs with a ...
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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. ...
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Unordered Set Classification Problem

In my setup I have one feature which is a sparse list representing categories. For example, let's say that we have M categories in the interval ...
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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}_{...
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When is sampling bias acceptable?

Overview: Dataset is small and a bit messy and the task is to classify 5 classes wherein the targets are ordinal. Feature Engineering and Selection, Model Tuning, etc. did not produce acceptable ...
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What is the reference time point relative to which the capital-gain and capital-loss features of the UC Irvine Adults dataset are measured?

The Adults dataset available in the UC Irvine Machine Learning Repository is based on the 1994 census data (USA census, I presume). The dataset has two features named ...
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Building a dataset for classification

I'm thinking of building a powershell script classifier using different architectures of neural networks. I have approximately 6k powershell scripts (3k malicious, 3k benign). My questions are: How ...
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Is GroupKFold needed if some samples have some of their feature values equal?

I am given a dataset $D$ of 10k enzyme-substrate complexes having a lock-key relationship, with each sample (complex) being characterized by enzyme features $x_e$ and substrate features $x_s$. That is,...
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Feature selection in binary classification

I have a dataset with two classes and am interested in learning which features are 'important' for predicting the class. There are a lot of features available and I want to find subset(s) that lead to ...
Shawn's user avatar
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Public Email Classification Dataset but not Spam vs Ham

Context Working to deliver a POC on automated email classification (in customer service context) to tag emails as related to feedback, complain, lost and found etc. The tags are not entirely exclusive,...
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What are approaches to identify the meaning of columns in a dataframe based on similarity to known column instances

In my domain we can perform upon to 12 tests on a substance, and record results for each of the tests at different pressures e.g. between 10 and 20 steps between 0 and 6000 psi. for each substance ...
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Measures of efficacy for one classification models on the same data set with different numbers of classes?

I am currently doing a university project in supervised learning. The variable to be predicted varies across the integers [0,100] and my supervisor suggested to split this range into different classes ...
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(Tensorflow) How to speed up initialization of model.fit()?

So I'm working with a rather large dataset (perhaps not really by ML standards - but too big to fit into my computer's RAM at any rate). And so, I train the model by successively loading a subsample ...
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Need to compare results using Ward's method

So I create clusters like this and StandardScale them ...
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How to improve Accuracy on dermaMNIST dataset?

Unlike the regular MNIST which gets 97-99% with a fairly basic network, dermaMNIST gets training/validation stuck on 0.69. This tells me the model is underfitting. But, making it bigger seems to have ...
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Group/cluster semantically similar classes in reports?

I'm fine-tuning BERT models to binary classify reports. For example, a report can be about 'birds' or not about 'birds'. This works really well, but now I want to do multi-label classification, ...
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How to classify/recognize postage stamp varieties?

As a hobbiest stamp collector, I often run into the need for classifying stamps based on minute differences, such as these: Now, I literally have thousands of them (in ziploc bags) and I am planning ...
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Can we calculate Bayes Error rate, if we have a simulated data?

I am going through ISL(Python) and in section 2.2.3 ( Page No. 36), the author writes, "For our simulated data, the Bayes error is 0.133. It is greater than zero, because the classes overlap in ...
Prashant Kumar's user avatar
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Calculate AUC-ROC and AUC-PRC for an LSTM Model

I have the following simple Bidirectional LSTM model for a binary classification task: ...
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Speaker Verification models on

I went through different articles of speaker verifications (ECAPA-TDNN, TITANET). They trained on ...
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Can someone interpret my Binary Cross Entropy Loss Curve?

I am trying to understand my loss curve using : tf.keras.losses.BinaryCrossentropy() Question 1: Based on my loss curve/accuracy, would it be wise to proceed to feed it into a ensemble learning model ...
Leibon Jarbis's user avatar
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Training the neural network does not give the expected result

I'm trying to create a pytorch neural network capable of recognizing peaks in 2D graphs. Previously, I was able to get a result close to what I wanted, but it was not ideal and did not give a ...
AlterEGO's user avatar
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Deal with overlapping classes in classification modeling

I am currently working with a dataset comprising information about crop insurance for soybeans. My ultimate goal with this dataset is to create a classification model capable of predicting whether ...
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Classification techniques for continuous arrays as inputs and scalar categorical variable as output

a newbie here. If you had any ideas about the following, that would be great. Suppose for a given data set: T’s and Y’s are arrays with T = [0 1 2 3 5 6 7] Y= [4 7 9 3 6 1] So at T=0, Y=4 and so on Z =...
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Implementing Fuzzy Matching and NLP for Transaction Classification

I’m a trainee at a fintech startup, and I’m working on a project that involves classifying transactions using Natural Language Processing (NLP) and fuzzy matching techniques. The main goal is to ...
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Do LSTM, GRU and Transformer models with less layers and units perform better than larger models when classifying short text sequences?

I am working with a Kaggle dataset with short Twitter messages as text input. I made a copy here. When testing LSTMS, GRUs, bi-directional versions of the GRUs, and the Encoder layers of a Transformer ...
Joachim Rives'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 ...
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Classifying Players as winners or losers

I have a dataset that I curated from a game that I play. There are currently 130 instances (i.e. players) and an innumerable number of features. Experience tells me <10 features would be sufficient....
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What are the drawbacks of utilizing sample weights in classification tasks?

In classification tasks, especially when dealing with unbalanced data, using sample weights can be beneficial. However, it's not always the default choice in ML libraries like AutoGluon ...
jsn's user avatar
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Similarity Scores between SQL tables

I'm trying to figure out the best way to get started on a project. I have two separate databases, one is a "Template" db and the other is "Content" db. For each table in the ...
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Rather than build a classification model, Is building an embedding regression model feasible?

Face recognition models like VGG Face are designed to have a classification head on top and then trained to classify face images, but after they are trained the classification head can be removed and ...
Ahmed Gamal's user avatar
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Data augmentation technique not working correctly

Write a function that can shift an MNIST image in any direction (left, right, up, or down) by one pixel.⁠6 Then, for each image in the training set, create four shifted copies (one per direction) and ...
samsamradas's user avatar
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Discuss kNN, test/train, random projection, unit vector, vectored matrix, hamming distance, stft, Y=(aAX1:M)

Suggestion Investigation Looking for suggestions or guide for how to setup a clean approach and discussion on how to apply a python suggested way to solve this challenge Looking for suggestions or ...
Data Science Analytics Manager's user avatar
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Reducing language bias for text classification, transformer model

I am working on a text classification model predicting classes for text. We have languages from many parts of the world and some of our classes are dominated by specific languages. The model we are ...
Carl Rynegardh'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, ...
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How to interpretmulti-class confusion matrix?

I'm looking at the SAMHSA Mental Health Client-Level dataset. I did some t-SNE plots (dropping irrelevant cols, normalizing some, one-hot encoding some) of 500k rows out of 6.5mil. I'm trying to do ...
Jackson Walters's user avatar
1 vote
1 answer
36 views

Find closest color class to an RGB value

I have a module that estimates the color of an object and returns an RGB value in this format: (40, 48, 68) which corresponds to this color: Now I have to classify ...
Mary'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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PR-AUC vs F1 vs Balanced Accuracy

I'm trying to create a Random Forest Classifier for selecting ~ 700 features. I have a highly imbalanced dataset to select features from. There are significantly fewer positive cases (1%) compared ...
user155775's user avatar
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Robustness and Sensitivity of Naive Bayes to Irrelevant Features

I understand that one of the strengths of Naive Bayes is its robustness to irrelevant features. However, it's also important to note that it can be sensitive to the presence of irrelevant features, ...
baddy's user avatar
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4 answers
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How can I scale my data for a machine learning model in a way that preserves the relationship between columns?

Lets take a simple database with 3 columns called x1, x2 and label for example label is being labeled by this condition if x1-x2> 0 then label = 1 else 0 , i.e <...
Rushabh Kheni's user avatar
1 vote
1 answer
50 views

Why my simple resnet model overfit?

I work on data classification. My train results are good 90%+ accuracy, but the test accuracy/loss is inconsistent. I don't succeed to get rid of the overfitting. The images are grouped, so to ...
J. Doe'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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i am trying to get the the variance of derivative of order 2. i only have the data of an EEG signal sampled at 128 Hz. is the below code correct

I basically want to implement equation 7 present in the added image ...
Shreedatta Nasik's user avatar
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How does ROC work with SVM?

Could someone please explain how ROC works with SVM? Specifically i'm using RocCurveDisplay.from_predictions(y_test, y_pred, ax=ax[1]) which works fine. Since the ...
lemintare's user avatar
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1 answer
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How to take the $\log$ of $e$ when taken to the power of a matrix?

I'm having some troubles trying to solve the following question, I'm trying to find the $C$ which maximizes $$\begin{align}\text{arg max}_{1\geq m\geq K}(\log p(\mathbf{x}|C_m)+log P(C_m))\end{align}$$...
Elliott de Launay's user avatar
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1 answer
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Each person gets their top, or second choice of activity over a period of 6 slots

We are running a camp for 130 children, and on 3 days they can pick different activities to do. One activities for slot 1 (45min), the other for slot 2 (another 45min), enabling them to do 6 ...
Pascal's user avatar
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Why do object detection model adversarial masks look different from those of image classifiers?

I was messing around to observe the behavior for adversarial attacks on image classifiers, and decided to try it with an object detector as well. I realize that inference time attacks are more complex ...
Soumil Datta's user avatar
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1 answer
39 views

How to optimize my CNN classification architecture

I have this CNN based model architecture that takes an RGB image. Now I'm trying to change it for a color classification case on an object (10 color classes: white, black, yellow, etc). This current ...
Mary's user avatar
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-1 votes
1 answer
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Is it possible to have different amount of features for the Classification decision in a support vector machine?

Is it possible to train a support vector machine with two classes using two features and then trying to make a decision for a new data object to which class it belongs that has the same two features ...
Johannes's user avatar

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