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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1answer
30 views

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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0answers
26 views

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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1answer
46 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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1answer
26 views

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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0answers
12 views

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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0answers
19 views

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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1answer
28 views

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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1answer
30 views

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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0answers
13 views

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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1answer
43 views

How does CURL extract labels from logits?

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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0answers
27 views

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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0answers
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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0answers
14 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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0answers
14 views

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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0answers
50 views

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-...
2
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1answer
49 views

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 ...
4
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1answer
87 views

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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0answers
57 views

How to use Product Matching to create Product Bundles

I am working on a product matching model. GOAL A store has many products like creams, perfumes, other beauty products. Based on product properties I have to create bundles of it so we can sell more ...
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0answers
18 views

Why does self-supervised representation learning (such as SimpleSiam) use a ResNet encoder that is trained in a supervised fashion?

Can anybody explain to me why does self-supervised representation learning on images using Siamese neural networks (such as SimpleSiam (https://arxiv.org/abs/2011.10566), SimCLR, Boyl) use a ResNet ...
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1answer
3k views

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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0answers
10 views

Is there any method that combines temporal action proposals with multiple actions' classifiers?

I am trying to classify actions in untrimmed videos. These videos contain a very imbalanced set of actions (where the background class is the majority). I have previously tried frame-wise action ...
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0answers
31 views

Interpreting a self organizing map resulting from the same dataset with different standard deviations

I am working on a task where the goal is to make a sofm learn a mapping from a three-dimensional space (the input space) to a two-dimensional space (the sofm "grid"). The data points are ...
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1answer
27 views

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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2answers
49 views

Accuracy metric for Clustering

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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0answers
16 views

Deep unsupervised clustering on big data with no prior knowledge

I have around 3 million BW images. I would like to organize them in as few clusters as possible in a way that is meaningful for the dataset without any prior knowledge for this data, as they come from ...
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1answer
54 views

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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0answers
38 views

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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1answer
50 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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1answer
365 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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1answer
82 views

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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0answers
92 views

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 ...
2
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1answer
64 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 ...
2
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1answer
167 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 ...
2
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1answer
52 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?
4
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2answers
248 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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1answer
40 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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0answers
37 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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0answers
57 views

How can I group the entries of the network traffic by their similarity?

I have the traffic of my network (with hundreds of entries). Below I am showing only 9 entries. ...
2
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1answer
56 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 ...
2
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2answers
63 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 ...
3
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6answers
75 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? ...
0
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1answer
129 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-...
2
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2answers
138 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 ...
3
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1answer
69 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?
1
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1answer
79 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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0answers
41 views

Training an unsupervised convolutional neural network to learn a general representation of a Lua module

I am trying to train a CNN in keras to learn a general representation of a Lua module, e.g. requires at the beginning, local variables, local functions, interface (returns) and in between some ...
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0answers
47 views

How is clustering used in the unsupervised training of a neural network?

How is clustering used in the unsupervised training of a neural network? Can you provide an example?
3
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1answer
83 views

In unsupervised learning, what is meant by "finding the probability of an image"?

The specific problem I'm having is with a Fully Visible Belief Network. It is an explicit density model (though I don't know what quantifies something being such) that uses the chain rule to decompose ...
5
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2answers
120 views

Unsupervised learning to optimize a function of the input

I am looking to build a neural network that takes an input vector $\mathbf{X}$ and outputs a vector $\mathbf{Y}$ such at $f(\mathbf{X}, \mathbf{Y})$ is minimized, where $f$ is some function. The ...
3
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1answer
490 views

Is there any Python library available for manifold learning using diffusion map? [closed]

I would like to use unsupervised learning with a technique called diffusion map based manifold learning in Python. The original paper on the diffusion map is An Introduction to Diffusion Maps. I have ...