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Questions tagged [unsupervised-learning]

For questions about AI that learns without being provided with a set of labels (expected answers) along with the set of input examples.

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I have a 3 class classification problem. Detection of one of classes is very important. How to design the problem? one class classification or ...? [closed]

I have a 3 class classification problem. Correct detection of one of the classes is very important. How to design the problem: one class classification? a normal 3 class classification? two distinct ...
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2 votes
1 answer
28 views

What clustering algorithms work best for datasets with only binary categorical features?

I have a dataset with a lot of binary categorical features and a single continuous target value. I would like to cluster them, but I am not quite sure what to use. In the past, I have used DBSCAN for ...
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Is there an unsupervised learning method for determine the most common questions within a dataset?

I have a dataset consisting of questions from customers. I am curious of the n most frequent asked questions, regardless of the variation the questions might appear in. Is there NLP methods for ...
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50 views

Is there a term for unquantifiably uncertain prior knowledge?

I'm working on a clustering algorithm which assigns each data point an index encoding its cluster. Index permutation is irrelevant to the correctness of the result. The algorithm is self-learning, in ...
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1 vote
1 answer
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Deep Features of Images - Better to use an unsupervised approach, or train a classifier with many classes?

I'd like to build a deep feature extractor of images (using a Bi-linear CNN). I was wondering what would lead to the best results: An unsupervised approach (such as https://iopscience.iop.org/article/...
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1 vote
1 answer
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What happens if all the features are correlated with each other before clustering?

I know that when two features are highly correlated with each other, one of them should be removed from the dataset so they don't add twice the weight. However, what if all my features share a ...
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Which rule could I use to identify suppliers who are likely to leave us or stay with us?

I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such ...
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2 votes
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What are the benefits of using spectral k-means over simple k-means?

I have understood why k-means can get stuck in local minima. Now, I am curious to know how the spectral k-means helps to avoid this local minima problem. According to this paper A tutorial on Spectral,...
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Unsupervised methodologies to detect collective anomalies in transaction data

I am researching various methodologies to detect collective anomalies in transactions data. I have seen some supervised approaches, but not the unsupervised ones. Please share any resources or ...
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How to group multi-dimensional audio, video, and numerical data based on relatedness?

I have a data set that includes image arrays, point clouds, audio waveforms, and plain numerical data. I want to use unsupervised learning to group the data based on relatedness. So, if the audio and ...
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Is it possible that k-means generates a cluster with no points in it, if the initial centroid is not properly set and no of cluster is large?

Is it possible that sklearn's k-means algorithm will generate a cluster that has no points at all, given that the number of k is large and the initial centroid is just random? Furthermore, will k-...
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1 vote
1 answer
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Test accuracy decreases during my train process

I want to train a neural network model with the arcface loss function and try to combine it with domain adaption. But when the training process continues, I find the test accuracy first increases and ...
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How to apply Deep Learning techniques to unlabeled data for Anomaly Detection

I'm fairly new to the field of deep learning and would like to ask which deep learning techniques can be used for anomaly detection in unlabeled data. For example, let's say I want to detect anomalous ...
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0 votes
1 answer
47 views

Generating a dataset from data with "assumed" lables

I've got a task similar to the following: Out of x amount of people, I need to predict, who could be a good athlete and who not. The thing is, I don't have data on the athletic performance of those ...
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In this example of fuzzy c-means, what is the difference between "sigma" and "center" for the clusters?

In this example, what exactly do "Cluster" and "Sigma" mean? (They chose random coordinates for the three centroids of the groups) Centers: Cluster centers, returned as a ...
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What is the difference between supervised and unsupervised training in T5?

I know unsupervised training for T5 is like: input: He went X output: X to school Z is this equivalent to the following in a supervised manner: ...
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Algorithm to separate audio source that Andrew Ng did in his ML Course

Hey I was doing the ML course of Andrew Ng's ML course. In a video he shows a algorithm that can separate two audio source and separate voice from music. Has any one tried such an algorithm? Though he ...
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-1 votes
1 answer
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What is the borderline between unsupervised learning and regular algorithms?

Unsupervised learning using neural networks is clearly machine learning since it is utilising neural nets. However, some algorithms, k-means clustering, for example, are considered unsupervised ...
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Is there a way to select the subset of most important features using PCA?

Is there a way to select the most important features using PCA? I am not looking for the principal components with the highest scores but a subset of the original features.
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Loss function to Push response value towards extremes

I have a feature map whose values are in the range of [0,1]. I want to push these values either towards extreme 0 or 1 using some loss function. Since I don't have any target value so it had to be in ...
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1 answer
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How does CURL extract labels from logits? [closed]

While going over the pseudocode of the CURL paper, the method to identify labels from the logits wasn't clear to me. I believe this technique might be common in other PyTorch/Deep Learning tasks. I ...
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What is the purpose of key - query matching in Momentum Contrastive Learning?

I am trying to understand the intuition behind the MoCo paper. How does the algorithm know if the key and query are crops from the same image?
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1 vote
0 answers
30 views

How to learn transition type in a 1-hour extended DJ Mix?

How would you design a model which learns the transitions in a given 1-hour DJ Mix? To be specific, the model should be able to learn transitions, specify the occurring time and the type (Crossfade, ...
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1 vote
0 answers
16 views

What is the best clustering method to detect anomalies for data with mostly categorical data?

I have a dataset with about 85 columns. Out of the 85 columns, 70+ are categorical. My goal is to identify the outliers in this dataset through clustering methods as I do not have a target column. ...
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1 vote
0 answers
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Can unsupervised models learn something from cat vocalizations?

I love cats, and over the years have noticed that they have recurrent patterns of vocalizations. For example, upon seeing a bird, a cat may start chittering, but the same cat would never chitter at ...
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2 votes
0 answers
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Does Yann LeCun consider k-means self-supervised learning?

I was discussing the topic of self-supervised learning with a colleague. After a while we realized we were using different definitions. That's never helpful. Both of us were introduced to self-...
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2 votes
1 answer
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Is there a clustering algorithm that can make n clusters and the n+1 "others" cluster?

As far as I know all clustering algorithms assume that all delivered data points have to find its cluster. My question is, is there an algorithm that could focus only on n clusters (number stated by ...
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4 votes
1 answer
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What is the relation between self-taught learning and transfer learning?

I am new to transfer learning and I start by reading A Survey on Transfer Learning, and it stated the following: according to different situations of labeled and unlabeled data in the source domain, ...
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2 votes
1 answer
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Is there a bias-variance equivalent in unsupervised learning?

In supervised learning, bias, variance are pretty easy to calculate with labeled data. I was wondering if there's something equivalent in unsupervised learning, or like a way to estimate such things? ...
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0 votes
1 answer
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Which algorithm can be used for extracting text patterns in tabular data?

I am working with tabular data that is similar to the below: Name Phone Number ISO3 Country Amount Email ... ... Outcome Possible Reason Leona Sunfurry (555)-555-5555 United States 58.96 leo_sun@...
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4 votes
2 answers
54 views

Which metric should I use to assess the quality of the clusters?

I have a model that outputs a latent N-dimensional embedding for all data points, trained in a way that clusters data-points from the same class together, while being separated from other clusters ...
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1 vote
1 answer
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Aside from specific training sets, what distinguishes the capabilities of different AI implementations?

(Disclaimer: I don't know much about ML/AI, besides some basic ideas behind it all.) It seems like ML/AI models can often be boiled down to statistics, where certain levers (weights) get fine-tuned ...
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2 answers
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Which models can I use for supervised learning with images?

I have to do a project that detects fabric surface errors and I will use machine learning methods to deal with it. I have a dataset that includes around six thousand fabric surface images with the ...
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1 vote
1 answer
56 views

How does dimensionality reduction occur in Self organizing Map (SOM)?

We have n dimension input for SOM and the output 2-D clusters. How does it happen?
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6 votes
1 answer
373 views

What is the “Hello World” problem of Unsupervised Learning?

As a followup to this question, I'm interested in what the typical "Hello World" problem (first easy example problem) is for unsupervised learning. A quick Google search didn't find any ...
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1 vote
1 answer
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What should the output of a neural network that needs to classify in an unsupervised fashion XOR data be?

XOR data, without labels: [[0,0],[0,1],[1,0],[1,1]] I'm using this network for auto-classifying XOR data: ...
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3 votes
0 answers
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NEAT can't solve XOR completely

I'm currently implementing the NEAT algorithm. But problems occur when testing it with problems which don't have a linear solution(for example xor). My xor only produces 3 correct outputs once at a ...
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2 votes
1 answer
71 views

Should forecasting with neural networks only be treated as a supervised learning (regression) problem?

I have recently made a work about the application of neural networks to time series forecasting, and I treated this as a supervised learning (regression) problem. I have come across the suggestion of ...
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2 votes
1 answer
270 views

Is this dataset with only two features suitable for clustering with k-means?

I am working with the K-means clustering algorithm for unsupervised learning. Is the following dataset suitable for the k-means clustering task or not? Why or why not? The dataset has only two ...
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2 votes
1 answer
59 views

When labelled data is not available, what are some common unsupervised learning algorithms for pattern recognition that can be used?

In pattern recognition systems, when no labeled data is available, what are some common unsupervised learning algorithms for pattern recognition, that can be used?
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4 votes
2 answers
282 views

How can reinforcement learning be unsupervised learning if it uses deep learning?

I was watching a video in my online course where I'm learning about A.I. I am a very beginner in it. At one point in the course, the instructor says that reinforcement learning (RL) needs a deep ...
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1 vote
1 answer
61 views

Applying Eligibility Traces to Q-Learning algorithm does not improve results (And might not function well)

I am trying to apply Eligibility Traces to a currently working Q-Learning algorithm. The reference code for the Q-Learning algorithm was taken from this great blog ...
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1 vote
0 answers
39 views

How do I approach this problem?

Let's say I have a dataset with multiple types of multiple ingredients (salt1,salt2, etc). Each n-th variation of each ingredient vs flavor may be represented by an n×k matrix that where an ingredient ...
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2 votes
1 answer
93 views

Is there a notion of generalization in unsupervised learning?

I've been learning a little bit about generalization theory, and in particular, the PAC (and PAC-Bayes) approach to thinking about this problem. So, I started to wonder if there is an analogous ...
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2 votes
2 answers
68 views

Could clustering be used to parse pdf documents to get headings and titles?

I'm a bit new to AI and I'd like to use some kind of clustering algorithm to solve a problem: I'm trying to parse pdf documents to get headings and titles. I can parse pdf to html and I'm then able ...
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3 votes
6 answers
78 views

How can I cluster this data frame with several features and observations?

How can I cluster the data frame below with several features and observations? And how would I go about determining the quality of those clusters? Is k-NN appropriate for this? ...
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0 votes
1 answer
182 views

What are the pros and cons of supervised, semi-supervised and unsupervised relation extraction in NLP?

I am following the NLP course taught by Dan Jurafsky. In the video lectures Supervised Relation Extraction and Semi Supervised and Unsupervised Relation Extraction Jurafsky explains supervised, semi-...
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2 votes
2 answers
192 views

How can I use autoencoders to analyze patterns and classify them?

I generated a bunch of simulation data from a complex physical simulation that spits out patterns. I am trying to apply unsupervised learning to analyze the patterns and ideally classify them into ...
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3 votes
1 answer
78 views

How to do machine translation with no labeled data?

Is it be possible to train a neural network, with no parallel bilingual data, for machine translation?
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1 vote
1 answer
102 views

Solving the supervised learning problem of learning $p(y \vert \mathbf{x})$ by using traditional unsupervised technologies to learn $p(\mathbf{x}, y)$

I am currently studying Deep Learning by Goodfellow, Bengio, and Courville. In chapter 5.1.2 The Performance Measure, $P$, the authors say the following: Unsupervised learning and supervised learning ...
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