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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15 views

LLE and ISOMAP, strange question and intrinsic low dimensional structure?

I prepare for PhD entrance exam on AI and one question is surprized me. which of the following techniques using intrinsic low-dimensional structure detection for dimension reduction? A) ISOMAP B) ...
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Reasons for a model predicting probability of being class 1 at x value

All, This is a general question. I have a binary classification which predicts if someone is rich or not. I had a question from someone asking that if the probability someone is rich is 0.6 and ...
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Looking for an algorithm to perform classification on multivariate grouped time series

I will be grateful for any help. I have multivariate time series, where every one of them has an unique ID. Also, there is a variable giving information about the trend type of the ID from a point of ...
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1answer
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AUC-PR but there is no recall or precision

Is it possible to have a Precision-Recall curve like this if your recall is zero and your precision is not defined? How do I interpret this? I have checked that all the scores are right and I still ...
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Can I send images + boundingboxes(as features) to an LSTM? How?

I have previously trained a YOLO v4 object detection model and I am looking to leverage the results(Bboxes) of this model and create another model to recognize/classify accidents in CCTV footage/video(...
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Should hexadecimal addresses of a dataset be cleaned?

I am working on fraud detection on blockchains. To be more specific, I fetched a big number of transactions that took place on the blockchain, labeled them to spam / non spam using an appropriate API ...
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How to classify (supervised) a multi dimensional vector?

What kinds of machine learning tool is used to classify a vector of data which are not spatially correlated? I have a 158*158 image*15000 samples which I tried to ...
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548 views

Which machine learning algorithms are more suitable for binary classification?

We know that there are many different types of classification algorithms. But among the different categories of classification algorithms, which algorithms are suitable for binary classification and ...
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26 views

Should I add string feature columns?

If my dataframe looks like this: ...
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Suggestions for binary time-series-classification model for small dataset

Hopefully I´m at the right place for my question: I´m looking for suggestions for models to use to classify multivariate time series. I´m trying to find a way of classifying the behaviour of motors ...
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1answer
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each class distribution in a classification problem

Can we tell that the distribution of each class differs and the distribution of dataset is the combination of the classes distribution? What can we infer about the class distribution?
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KL divergence as loss for classification

I want to use KL-divergence as a loss function for classification problems. For example, consider the dog and cat image classification problem where I designed a CNN model with Softmax as output layer ...
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Threshold moving for classification - how can i assess the cost?

I have a binary classifier. When i used my model to make predictions about 4k out of 10k were predicted to be "Rich". I am predicting affluence. Normally in classification the cut off to ...
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Important features for detecting malware on the network

I am trying to build a model (Machine Learning) in order to detect malicious network traffic. At first, I am trying classify network traffic as malware or benign. After predicting the malware part, I ...
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Points to remember when embarking on an organization-wide turn to AI solutions

In our organization, we are currently in the phase of building up team, skills to automate and implement AI based solutions. So, we are very early in this AI journey. Right now, we are also working on ...
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281 views

Imbalanced Dataset: Train/test split before and after SMOTE

This question is similar but different from my previous one. I have a binary classification task related to customer churn for a bank. The dataset contains 10,000 instances and 11 features. The target ...
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CutMix VS Mixup Data Augumentation method for end-to-end deep learning Traning

I am looking for arguments on which Data augmentation (Mixup VS CutMix) method would be preferable for Image data and Time-series classification data. As for as I know, both have the following ...
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How to generate classification rules using only positive values

Problem Description I have a survey data set that I want to use for a classification problem. In short respondents are grouped split along a binary target variable into "1" - part of the ...
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29 views

Word classification

I have a task to classify the model of a product from its part number using machine learning. Part numbers can be of different lengths and forms and can contain both letters and numbers and also ...
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Any transformer model (NLP) for code classification?

Does any Transformer (NLP) that is suitable for code classification tasks exist? For example, I have a lot of source codes of various categories (driver, game, email client, etc.). I want to ...
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438 views

Good classifiers when having many labels

I am asking myself, if there is another good method than deep artificial neural networks when trying to classify data with many (>100) labels. Are there any suggestions? For example, logistic ...
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50 views

Imbalanced classification task – Discrepancy between learning curves and test set evaluation

I have a binary classification task related to customer churn for a bank. The dataset contains 10,000 instances and 11 features. The target variable is imbalanced (80% remained as customers (0), 20% ...
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default prediction. What does a model look like?

There is a data set in the ISLR package that deals with student loan defaults You basically have 3 predictor columns: credit card balance, whether or not individual is a student, and the balance of ...
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1answer
29 views

Why not LinearClassifer when RidgeClassifier works?

Recently I came across this model called RidgeClassifier, It coverts the predicted value (y) to {-1,1} and then uses the Ridge Regression. During prediction if the value of y is < 0 then it is ...
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What is a good few-shot classifier function?

Is there any pre-written library or function which can receive a few examples of data values being classified and then extend that to new data values received?
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Browser history segmentation

I'm trying to segment a browser history into semantically coherent sessions. For example, a user might be working on a school project for 30 minutes, then planning an upcoming vacation for 30 minutes, ...
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Object Detection, custom dataset, algorithm [closed]

I'm looking for a solution to detect objects and classify them, using a custom dataset.The overall goal is to detcet objects using my webcam. So far I've wanted to use YOLO in combination with OpenCV, ...
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feature encoding for numerical features that depend on binary feature

I am working on a bounding box localisation problem where I need to detect whether a particular object is in an image, and if it is, I need to regress the coordinates of the bounding box. Currently, ...
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Test data relevance to a model (covariate shift)

I am trying to design an algorithm that will allow to calculate the relevance of test data to a trained model. This can be done by checking if predictor variables have a different distribution in ...
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Feature Importance interpretation

I want to audit the results of regressions I ran, and hopefully gain more insights about a treatment effect through sklearn's feature importance function (...
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Take uncertainty into account

If we have an error for each data. Is it possible to take these errors into account for the training and also maybe for the prediction? For example: ...
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Constructing heterogeneous datasets

Based on the "Dynamic Ensemble Selection Methods for Heterogeneous Data Mining" paper published by Chris Ballard and Wenjia Wang, I would be grateful if you could guide me on how they ...
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How to make Support Vector Machine source code without using libraries in R? [closed]

I want to estimate w and b using loops and functions. I also want to predict new variables. I need simple scratch code to understand the mathematics behind the Support Vector Machine.
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362 views

How to classify using incomplete features

Assume we have some features pressure, volume, temperature, intensity, mass, size, ... The problem is that, I do not have allways a complete set of these info. I can not put zero for the unknown ...
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Algorithm/method for grouping items based on their relative distance

I'm looking for a method to classify a set of items based on their relative distance. For example assume we have 4 cities and we know their relative distance: city1 city2 city3 city4 0 2.1 2.2 3.4 ...
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When performing token-classification over phrases, is it better to predict 1 by 1, or few at once?

Say you fine tune a pre-trained BERT model for token-classification. Which of the following method is best? Set a big FC layer to predict tokens for each token in the input sequence. Set the FC layer ...
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1answer
38 views

Logistic Regression - Probabilistic intuition vs Geometric intuition

The Probabilistic approach of logistic regression involves the MLE (Maximum Likelihood Estimation) maximizing the likelihood function, or in other words, finding the best parameters for the best fit ...
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How to determine which classes are easier to predict with a decision tree?

So, I'm trying to work with decision trees on Iris dataset. I've noticed by trying out different parameter (max_depth, leaves etc) that some of the classes are easier to predict (most of the trees ...
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1answer
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Overlap between the training and testing set in cross validation settings

Why is it important to evaluate models using a cross-validation setting where the training and test sets have no overlap? I noticed that a violation of this guideline exaggerates the effectiveness of ...
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Train Test Split for Imbalance Data set for credit card transaction data set

I am currently working on a credit card transaction datasets for fraud detection, and I am unsure how to go about splitting the data. Transactions are time related data, do I split them like how you ...
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102 views

Classification when the classification of the previous itens matter

I have a classification problem to solve, that seems to be common but I am struggling to find the name of this task and the best way to model this problem. Suppose I have a series of events that are ...
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1answer
21 views

Does class weighting encourage overfitting when the true class distribution is imbalanced?

I am working on a classification problem in which ~90% of samples come from class 1 while ~10% of samples come from class 2. I have been using various techniques to combat the class imbalance while ...
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Right way to compare model scores for Next Best Action

I have around 15 classification models for different products built in different ways (some are RF, some are Gradient Boosting, some were downsampled in one way, others in other way, some are built in ...
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Problem Direction - Text Data - Conversation Classification

The problem I have a problem where I have text data that has been transcribed from a conversation. These conversations have been marked as a pass or fail in terms of compliance by a person, ie they ...
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Speech/Voice Detection in Audio Files

I have several hundred 30 second long WAVE Files. I need a way to find out, if there are spoken words / voices / speech in them or not. E.g.: 1.wav no; 2.wav yes; 3.wav no (boolean) or 1.wav 0.21; 2....
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38 views

Using model's prediction score as movement quality evaluator

Let's take the task of evaluating very short dance movements (phrases) using sensor data (accelerometer and gyro from an iPhone device) as an example. If the model's confidence is 100% on a particular ...
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1answer
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How to deal with over confident model?

I have an LSTM model for action recognition. During inference, any random actions that are not labelled or the model has not learned at all are also predicted with very high confidence score. I ...
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32 views

Random predictions from a multi-label image classification model

I am currently trying to create a model for multi-label image classification using Keras. The model has 8 classes, with a slight imbalance in the dataset (some have 300~, whereas some others have 600~)...
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34 views

how to perform clustering using dtw and some clustering method like kmeans

I have a timeseries(temperature of a sensor)and I want to apply an unsupervised clustering that. I've already done that using sklearn library and Kmeans. but the problem is that I don't know how to ...
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Predict recovered amount of credit?

I would like to understand which is the best Machine Learning approach (regression, classification, ...) in the following scenario: I have a dataset with hundreds of people, each of them with a credit ...

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