Newest 'unsupervised-learning' Questions

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1answer

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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 ...

asked Apr 8 at 10:51

Makintosz

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35 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 ...

python unsupervised-learning recommender-system clustering scikit-learn

asked Mar 19 at 15:11

sogu

1015 bronze badges

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8 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 ...

terminology unsupervised-learning feature-learning self-supervised-learning siamese-neural-network

asked Mar 18 at 10:15

user3352632

3111 silver badge5 bronze badges

1

vote

1answer

12 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? ...

variance unsupervised-learning

asked Mar 16 at 16:20

user98235

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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 ...

computer-vision reference-request papers unsupervised-learning algorithm-request

asked Mar 4 at 10:19

SilicoMar

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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 ...

unsupervised-learning matlab clustering

asked Mar 2 at 10:00

Rim Sleimi

954 bronze badges

0

votes

1answer

24 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@...

unsupervised-learning pattern-recognition text-classification algorithm-request

asked Feb 25 at 18:51

Petar Luketina

1033 bronze badges

3

votes

2answers

39 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 ...

unsupervised-learning clustering accuracy

asked Feb 9 at 21:06

jaeger6

1686 bronze badges

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vote

1answer

40 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 ...

machine-learning reinforcement-learning models unsupervised-learning supervised-learning

asked Dec 9 '20 at 23:37

Fly

1111 bronze badge

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0answers

36 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 ...

neural-networks machine-learning unsupervised-learning autoencoders supervised-learning

asked Nov 20 '20 at 14:01

Ali Haydar Kurban

1

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1answer

45 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?

machine-learning unsupervised-learning self-organizing-map

asked Oct 4 '20 at 4:35

RCvaram

2567 bronze badges

5

votes

1answer

345 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 ...

unsupervised-learning

asked Sep 14 '20 at 6:29

Christian Aichinger

1533 bronze badges

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0answers

13 views

Finding Cycles in a State Sequence

Suppose I observe a set of states $\mathbf{X} = \{X_{1}, X_{2}, \ldots, X_{K}\}$ over time. I assume that there exist $M$ cycles $\mathbf{C} = \{C_{1}, C_{2}, \ldots, C_{M} \}$ in the observed state ...

machine-learning recurrent-neural-networks unsupervised-learning markov-chain hidden-markov-model

asked Aug 6 '20 at 17:31

The Dude

1011 bronze badge

1

vote

1answer

68 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: ...

neural-networks machine-learning deep-learning unsupervised-learning autoencoders

asked Jul 22 '20 at 5:57

datdinhquoc

9805 silver badges22 bronze badges

2

votes

0answers

65 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 ...

machine-learning evolutionary-algorithms unsupervised-learning neat

asked Jul 19 '20 at 18:46

Creepsy

1212 bronze badges

2

votes

1answer

61 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 ...

neural-networks reinforcement-learning unsupervised-learning forecasting semi-supervised-learning

asked Jul 9 '20 at 22:34

David Díaz

235 bronze badges

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0answers

38 views

How to train an Encoder-Decoder LSTM for sequence to sequence prediction?

I have a dataset where for each country there is a name (string) and a multivariate time series (all integers). I am trying to use an Encoder-Decoder LSTM to forecast the next time steps in the time ...

long-short-term-memory unsupervised-learning supervised-learning time-series forecasting

asked Jun 12 '20 at 13:17

Marcus

1233 bronze badges

2

votes

1answer

82 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 ...

datasets unsupervised-learning data-science clustering k-means

asked May 17 '20 at 22:31

Debugger

612 bronze badges

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0answers

18 views

How would one modify CycleGAN in order to map a distribution to itself?

CycleGAN can map between two different distributions $X$ and $Y$ with cycle consistency. This is done with generator functions $F: X \mapsto Y$ and $G: Y \mapsto X$, such that $||G(F(x)) - x||_1 \...

deep-learning unsupervised-learning generative-adversarial-networks image-generation

asked May 16 '20 at 18:44

Alexander Soare

1,0324 silver badges15 bronze badges

2

votes

1answer

43 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?

algorithm reference-request unsupervised-learning pattern-recognition

asked May 5 '20 at 16:48

Steven M

234 bronze badges

4

votes

2answers

190 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 ...

deep-learning reinforcement-learning terminology unsupervised-learning supervised-learning

asked May 4 '20 at 11:56

Lucas Vital

533 bronze badges

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1answer

36 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 ...

reinforcement-learning q-learning unsupervised-learning eligibility-traces

asked May 2 '20 at 20:18

Sahar Attia

112 bronze badges

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0answers

35 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 ...

machine-learning math unsupervised-learning clustering

asked Apr 29 '20 at 15:39

mightychrysanthemum

111 bronze badge

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votes

0answers

55 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. ...

machine-learning unsupervised-learning pattern-recognition data-preprocessing clustering

asked Apr 24 '20 at 4:50

nonosehahaha

11 bronze badge

2

votes

1answer

42 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 ...

machine-learning unsupervised-learning generalization pac-learning

asked Apr 19 '20 at 2:28

Marcel

1233 bronze badges

2

votes

2answers

58 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 ...

machine-learning natural-language-processing unsupervised-learning clustering

asked Apr 17 '20 at 15:01

Wylex

1212 bronze badges

3

votes

6answers

74 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? ...

python datasets unsupervised-learning clustering

asked Apr 12 '20 at 3:41

tosiful islam

312 bronze badges

0

votes

1answer

78 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-...

natural-language-processing comparison unsupervised-learning supervised-learning semi-supervised-learning

asked Mar 25 '20 at 11:07

D_Raja

8851 gold badge5 silver badges12 bronze badges

1

vote

2answers

68 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 ...

image-recognition keras unsupervised-learning autoencoders dimensionality-reduction

asked Mar 4 '20 at 8:30

Pavan Inguva

511 bronze badge

1

vote

1answer

55 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 ...

unsupervised-learning supervised-learning probability-distribution conditional-probability

asked Feb 25 '20 at 10:40

The Pointer

2902 silver badges13 bronze badges

1

vote

0answers

34 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 ...

convolutional-neural-networks tensorflow keras unsupervised-learning

asked Feb 24 '20 at 12:07

Michael Kročka

513 bronze badges

1

vote

0answers

45 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?

neural-networks machine-learning unsupervised-learning clustering

asked Jan 19 '20 at 11:40

Ramedlaw Vocinnas

215 bronze badges

3

votes

1answer

67 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 ...

unsupervised-learning

asked Dec 6 '19 at 10:57

Recessive

1,0111 silver badge14 bronze badges

2

votes

1answer

42 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 ...

neural-networks unsupervised-learning

asked Nov 20 '19 at 22:24

Y.Z.

212 bronze badges

3

votes

1answer

309 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 ...

python unsupervised-learning geometric-deep-learning resource-request scikit-learn

asked Nov 15 '19 at 17:38

Rahul

1334 bronze badges

3

votes

1answer

104 views

What needs to be done to make a fair algorithm?

What needs to be done to make a fair algorithm (supervised and unsupervised)? In this context, there is no consensus on the definition of fairness, so you can use the definition you find most ...

asked Nov 14 '19 at 9:25

jennifer ruurs

5291 silver badge7 bronze badges

4

votes

1answer

46 views

Are there methods that allow deep networks to learn object categorization in a self-supervised way?

When training a deep network to learn object classification from a set like ImageNet, we minimize the cross entropy between the ground truth and the predicted categories. This is done in a supervised ...

deep-learning object-recognition unsupervised-learning

asked Oct 12 '19 at 18:53

Wolphram jonny

1911 silver badge8 bronze badges

6

votes

1answer

79 views

How does the network know which objects to track in the paper “Label-Free Supervision of Neural Networks with Physics and Domain Knowledge”?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...

neural-networks machine-learning unsupervised-learning papers

asked Sep 18 '19 at 15:29

sanjeev mk

1611 bronze badge

3

votes

1answer

35 views

Do the eigenvectors represent the original features?

I've got a test dataset with 4 features and the PCA produces a set of 4 eigenvectors, e.g., ...

unsupervised-learning features principal-component-analysis

asked Sep 9 '19 at 14:16

Crizly

1311 bronze badge

1

vote

0answers

627 views

Which approaches are best suited for text deblurring?

I want to deblur text images using deep learning. Which approaches are best suited for the task? Any example networks? Is unsupervised network the best approach? GAN or cycle GAN for these purposes? ...

neural-networks convolutional-neural-networks unsupervised-learning generative-adversarial-networks

asked Sep 9 '19 at 7:43

Bot_Start

113 bronze badges

2

votes

1answer

113 views

Is unsupervised learning a branch of AI?

From Artificial Intelligence: A Modern Approach, a book by Stuart Russell and Peter Norvig, this is the definition of AI: We define AI as the study of agents that receive percepts from the ...

definitions unsupervised-learning clustering

asked Aug 29 '19 at 15:41

malioboro

2,3551 gold badge9 silver badges35 bronze badges

0

votes

2answers

48 views

How can I cluster based on the complementary categories?

K-means tries to find centroid and then clusters around the centroids. But what if we want to cluster based on the complement? For example, suppose we have a group of animals and we want to cluster ...

machine-learning unsupervised-learning clustering

asked Aug 28 '19 at 17:02

user3180

5002 silver badges10 bronze badges

3

votes

1answer

84 views

Is unsupervised disentanglement really impossible?

In Locatello et al's Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations he claims to prove unsupervised disentanglement is impossible. His entire claim is ...

unsupervised-learning knowledge-representation proofs papers

asked Aug 12 '19 at 0:38

mshlis

2,1374 silver badges21 bronze badges

1

vote

1answer

372 views

What is the role of the 'fuzzifier' w in Fuzzy Clustering?

According to my lecture, Fuzzy c-Means tries to minimize the following objective function: $$J(X,B,U)=\sum_{i=1}^c\sum_{j=1}^n u_{ij}^w \, d^2(\vec{\beta_i},\vec{x_j})$$ where $X$ are the data ...

unsupervised-learning fuzzy-logic k-means clustering

asked Jul 23 '19 at 15:18

user9007131

536 bronze badges

2

votes

1answer

57 views

Is a multi-layer Kohonen network possible?

The Kohonen network is one fully connected layer, which clusters the input into classes by a given metric. However, the one layer does not allow to operate with complex relations, that's why deep ...

neural-networks unsupervised-learning

asked Jul 17 '19 at 17:11

user8426627

3641 silver badge11 bronze badges

1

vote

0answers

18 views

Predicting Hot Categories In a Reference Manager

Reference managers like Zotero or Mendeley allow researchers to categorize papers into hierarchical categories called collections. The User navigates through a listing of these collections when filing ...

unsupervised-learning prediction reference-request markov-chain hidden-markov-model

asked Jun 29 '19 at 5:37

Max Suica

111 bronze badge

1

vote

0answers

278 views

How can I use the bottleneck layer of the U-net to calculate the similarity between two images?

I would like to use the bottleneck layer of U-Net (the last layer of the encoder) to calculate the similarity between two images. For that, I have to somehow flatten the last layer of the encoder. In ...

convolutional-neural-networks unsupervised-learning u-net

asked Jun 19 '19 at 4:25

oezguensi

2051 silver badge7 bronze badges

1

vote

0answers

22 views

Prediction of values with an unsupervised model

Given a set of historical data points, I am trying to predict a continuous output of which I have no historical record of, therefore the problem is of an unsupervised nature. I am wondering if there ...

models unsupervised-learning

asked Jun 8 '19 at 22:58

harold_sincere

111 bronze badge

3

votes

2answers

161 views

How can auto-encoders compute the reconstruction error for the new data?

Autoencoders are used for unsupervised anomaly detection by first learning the features of the data set with mainly "normal" data points. Then new data can be considered anomalous if the new ...

unsupervised-learning autoencoders anomaly-detection

asked May 29 '19 at 8:19

Brian

1312 bronze badges

5

votes

2answers

463 views

Is there a machine learning algorithm to find similar sales patterns?

I have a dataset as follows (and the table extends to include an extra 146 columns for companies 4-149) Is there an algorithm I could use effectively to find similar patterns in sales from the other ...

machine-learning unsupervised-learning linear-regression pattern-recognition k-means

asked May 16 '19 at 8:51

Anonymous

533 bronze badges

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