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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Single model or multiple models for predicting at each level in a multi-level classification problem
Given a flat structured data with features that can be considered hierarchical, where each feature is at a different level (e.g., Brand at the top level, Product, Color, and Size at different levels), ...
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Integrating time context in a machine learning model
Basically, what I'm curious about, are there any methods in machine learning to make the model take into account events that happen in real time that affect the data points during that time period. ...
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Understanding correlation - Machine Learning
I am experimenting a project on identifying cancer or not - Binary classification
The dataset has many columns. Here, I added correlation values between few input columns and the target column[cancer/...
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Do models of social systems suffer from prediction drift?
Background
I've created a binary classification model that predicts the probability of fraud for a given sample.
The choice of threshold allows me to set how many frauds are captured in the training ...
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How can I use machine learning to identify groups in social deduction games?
I'm trying to write an algorithm to identify evil factions in the game Town of Salem. In Town of Salem, the mafia have to take over the town. The rest of the town (townies) must prevent this. To do ...
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How can i implement an confucion matrix?
im trying to do a research but i need to make a confusion matrix how can i do that on this model?
https://www.kaggle.com/code/stpeteishii/race-classify-densenet201
Sorry im so so new to everything.
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What are some approaches to improve the classification of ONE particular instance of interest?
I'd like to know if there are some methods to correct a specific misclassified instance of interest (e.g. in a Logistic Regression or Random Forest).
Like maybe increasing the error for that ...
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Feature engineering for interest-based age classification
I have a dataset which has users (rows) with the list of their interests (IABs), which looks like this
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Example of a 2D dataset and a classifier stuck at local minimum
We always hear about neural networks getting stuck at local minima, but I cannot visualize one. Can you please give me some examples?
I am not looking for something like below picture and a neural ...
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Classification problem with a numerical variable that uses a special (high) value to indicate a qualitatively different status
I have a classification problem where I need to predict an outcome based on 20+ variables, some categorical, some numerical. One of the numerical variables is 'dlast' - which is the number of days ...
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Is it valid changing the classification treshold of neural networks for improving the classification performance?
I'm dealing with text classification using BERT pre-trained model with a multiclass imbalanced dataset.
When we use a 0.5 default classification threshold we obtain a f1 measure of around 0.7.
But we ...
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What models are able to handle variable input lengths?
I am tasked with creating a classifier that is able to predict whether an item will be returned.
This is supposed to not only happen on the basis of an individual item, but on all other items within ...
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How to Manipulate a Dataset
I have a raw dataset of Images I got from Kaggle, It has been classified already, but I want to randomly split the information in a 80:20 ratio between train and test, problem is since all information ...
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Is deep learning high initial validation accuracy a sign of problem?
I have a image classification model with 8400 images of class A and 1800 images of class B. I have used validation_split=0.2 with subsets of ...
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Help with gamers' model: Is there an special name for a classification model in which the positive case is certain but the negative case is uncertain?
Suppose that I possess a binary classification model, where the positive class is certain, and I am confident that the positive samples belong to that class, while the negative class is uncertain, as ...
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Classification Algorithms for Geospatial Vector Data
I am new to the world of Geospatial Analysis.
As such, I am interested in Machine Learning / Deep Learning techniques for classifying geospatial vector data specifically (as opposed to raster data). I'...
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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 ...
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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 ...
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Time series Classifiction - is LSTM better than XGBoost
My question is whether LSTM RNN is a better predictor of an label (note not forecaster) than XGBoost. Thus far I have had moderate success with XGB but I wonder if the tree nature, random start and ...
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Should I use Boruta feature selection if I'm comparing two datasets?
I'm a beginner to machine learning and AI so I really could you some guidance on this.
I am currently comparing two different datasets with different classification algorithms. One of the datasets has ...
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Classification of a noisy data
What method can be used to classify data in the following example?
There is a table (hundreds of strings and hundreds of columns). Several columns in this table uniquely allow you to classify each row:...
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Imbalanced performance metrics in binary classification
I am developing a binary classification model using sklearn pipeline for preprocessing and a soft voting classifier (Adaboost and Extratrees with 50 estimators). The dataset (3 million rows) contains ...
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Which algorithms are suitable for time series classification for this form of data?
Newbie here, I have a large list of csv files that contain a series of probability distributions (for 5 classes). I'm trying to train a binary classifier that classifies each file into either a ...
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Intuition behind replacing constraint in equation for Optimal Separating Hyperplane
I am reading "Optimal Separating Hyperplane" section of the book - Elements of Statistical Learning which is described on page 132 as follows:
My questions:
The constraint $||\beta|| = 1$ ...
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What do I make of all classification scores being equal to 1?
I've built an XGBoost classifier on a dataset that has 51 columns and a 1000 rows with following code:
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Tuned model has higher CV accuracy, but a lower test accuracy. Should I use the tuned or untuned model?
I am working on a classification problem using Sci Kit Learn and am confused on how to properly tune hyper parameters to get the "best" model.
Before any tuning, my logistic regression ...
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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 ...
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how to define observation and event window
In a retail use case where I don't have a customer end date, so I tried to come up with a logic of taking the max difference within 1 year b/w consecutive purchases and based on a certain threshold ...
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Is classification enough for this?
I have a DB with 2 tables connected with a one to many relationship. Let's say one of A is linked to many of B. The tables have both two fields for a date and some text. And both tables get new ...
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How does cross-entropy loss change with the number of classes?
How does the value of the cross-entropy loss function vary with the number of classes being predicted?
Formally, if the loss function is
$$
L = - \sum_{x \in X} P^*(x) \log P(x)
$$
where $P^*(\cdot)$ ...
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Approaching multiple records for one observation; radiomics of 2D slices of a 3D object
Background
I am trying to create a model that can predict Type 2 diabetes in a patient based on MRI scans of their thigh muscle. Previous literature has shown that fat deposition in the muscle of ...
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help interpreting training/validation curves for classification tree
I'm developing a binary classification tree and having some touble interpreting my training/validation curves. I used the CART algorithm with information gain as my splitting criterion. The training ...
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Is it necessary to have an additional "None" class for classification tasks for unknown inputs?
The idea is to have an additional class that would be "triggered" whenever there's an unknown/ambiguous input. Ideally, a ML model should do this by itself: it should for example return ...
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Classification-Problem based on limited Dataset (Need keywords to search/ reading recommendations)
I have a dataset of about 200 test subjects, each with age, testscore and a one of two possible traits. I want to define some kind of function, where I input age and testscore, that predicts which of ...
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Transformer doesn't generalize on a time-series data
Data
120 patients.
Each patient has 5.7556e+06 samples on average, each sample consists of 5 features stored as a continuous high-frequency (1000Hz) time series.
Labels are 13 discrete classes ...
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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 ...
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Binary Classification [Text] based on Embedding Distance?
I was just informed this community was a better fit for my SO question. I am wondering if I can use a Milvus or Faiss (L2 or IP or...) to classify documents as similar or not based on distance. I have ...
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How to calculate accuracy of a logistic regression?
A logistic regression involves a linear combination of features to predict the log-odds of a binary, yes/no-style event. That log-odds can then be transformed to a probability. If $\hat L_i$ is the ...
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Train multiple models to predict subsets of classes in data
If you are aiming to predict a number of classes that may be too high for the available data, is there any merit to training multiple models to predict a subset of the classes, each, and combining the ...
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Oddly classifier is more accurate than regressor for solving a regression problem - what could be happening?
I am working through a simple tabular supervised machine learning problem.
I have a continuous target variable y that is normalized to the interval 0-1 to represent ...
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Classification of sequential data
I'm currently trying to classify discrete sequential data into five classes with machine learning.
The setup is the following:
The actual object is filled with various properties, but to separate the ...
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What method should I use to see whether my categories are well-encoded by my variable?
In order to test some linguistic hypotheses, a friend of mine looked at some words in some text and tries to see what tests can one do to predict in which category the word belongs.
The data format is ...
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How to present a statistical justification for the choice of models with approximate accuracies?
In an experiment involving the comparison of classification algorithms, how can I assess whether there are statistically significant differences between the analyzed models? For example, the following ...
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How to handle imbalance in input variables?
Currently working on a finance dataset which has more than 20 input variables with high imbalance.
[Apparently, the target variable is also imbalanced (for this I am currently considering to handle it ...
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Probability distribution of probabilities
We can get the prediction probabilities of a binary classifier from sklearn's API using the predict_proba method. Is it reasonable to expect that the shape of a histogram plotted for the prediction ...
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Classify E-commerce URLs into predefined classes
How can I classify an E-commerce URL Page into the following categories,
Cart
Payment
Product Page
Checkout
How can I achieve this with the url and page title in my hand? I have tried multiple ways ...
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How to perform a classification experiment with data augmentation?
I'm working on an audio classification experiment. In my original database, I have 1,412 records. To improve the performance of my models, I resorted to data augmentation, applying simple techniques ...
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How to increase retention?
As you might already know there is a concept of retention. Let's say I have created a game and today hundred people have downloaded my game. Let's say tomorrow 47 out of yesterday's hundred people are ...
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fann gives me too many bit fail while training with company financial data
I am trying to train neural network with FANN (in ruby) to propose where should new company belong to.
As a source I have financial values for already categorized companies like ebitda, revenue, cagr, ...
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Difference between recommender system and appetency score
I'm wondering about the difference between the recommendation system and the appetency score. I already know that the appetency score is a binary classification problem for one product where we try to ...
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