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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.

41 questions with no upvoted or accepted answers
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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. ...
sanjeev mk's user avatar
4 votes
1 answer
332 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 ...
Creepsy's user avatar
  • 141
3 votes
0 answers
227 views

What are examples of good reference books on unsupervised learning?

I am looking for good introductory and advanced books on unsupervised learning. I have already read books like Probabilistic Graphical Models from D. Kholler and Pattern Recognition and Machine ...
Ecterion's user avatar
2 votes
0 answers
27 views

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,...
Amartya's user avatar
  • 121
2 votes
0 answers
176 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-...
Pieter's user avatar
  • 121
2 votes
2 answers
550 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 ...
Pavan Inguva's user avatar
1 vote
0 answers
35 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, ...
Cactuser's user avatar
1 vote
0 answers
21 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. ...
user13074756's user avatar
1 vote
0 answers
21 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 ...
Alex Stone's user avatar
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 ...
mightychrysanthemum's user avatar
1 vote
0 answers
66 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 ...
Michael Kročka's user avatar
1 vote
0 answers
50 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?
Ramedlaw Vocinnas's user avatar
1 vote
0 answers
952 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? ...
Bot_Start's user avatar
1 vote
0 answers
36 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 ...
Max Suica's user avatar
  • 111
1 vote
0 answers
648 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 ...
oezguensi's user avatar
  • 205
1 vote
0 answers
26 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 ...
harold_sincere's user avatar
1 vote
0 answers
24 views

Is there a way to compare the similarities among different graphs and then cluster them using Unsupervised learning?

I have a dataset about (240000,23). For my task, I have to use an unsupervised learning method and apply it on every single column separately in order to detect anomalies that might exist. I have pre-...
zeeman's user avatar
  • 111
1 vote
1 answer
122 views

Are there any advantages of using rules-based approaches versus models for detecting spam?

Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a ...
rulesguy's user avatar
1 vote
0 answers
46 views

identifying pattern in datasets

i am new to machine learning. i'm trying to identify driving pattern through accelerometer and gyroscope sensor. i have been collecting the data of both the sensors and have been storing them in .csv ...
Anif Zarus's user avatar
1 vote
0 answers
34 views

a question about Zeiler's paper “Deconvolutional Networks”

In "4.1 Learning multi-layer deconvolutional filters" section, the last paragraph says that "Since our model is generative, we can sample from it. In Fig. 3 we show ...
fanxukong's user avatar
1 vote
0 answers
87 views

Learning from events. Supervised, Unsupervised or MDP?

I have a large set of simulation logs for a market simulation of which I want to learn from. The market includes: customers products (subscriptions) The customers choose products and then stick with ...
pascalwhoop's user avatar
1 vote
0 answers
36 views

Does it make sense to train an autoencoder using data from different distributions?

Say I have 500 variables and I believe those variables can be shown in a 4-dimensional latent representation which I want to learn. What I have for training is 100K samples, and those samples are ...
user5054's user avatar
  • 151
1 vote
1 answer
65 views

Is there an LSTM-based unsupervised learning algorithm to label a dataset of curves?

I have a big amount of light curves (image below). I am trying to label the points as signal or background (the signal appears usually periodically, several times, for a given light curve). More ...
Alex Marshall's user avatar
0 votes
0 answers
10 views

Linear dependency between features on unsupervised learning

I am preparing a numerical dataset to be trained using unsupervised learning methods (i.e. association with Apriori algorithm) in order to try to find instrinsic correlations hidden in the data. ...
FELIPE_RIBAS's user avatar
0 votes
0 answers
12 views

How to knowing number of clusters when using SOM?

SOM uses neural network. The output layer of SOM should be neurons position. As the model is training, neuron's position started to moving to the closer of centroid of clusters. The output layer was ...
Muhammad Ikhwan Perwira's user avatar
0 votes
0 answers
29 views

Which main steps should I consider in order to successfully use a VAE for Anomaly Detection?

I am thinking about using the variational autoencoder model for anomaly detection . I have an Android Logs dataset. As the logs generated are a representative of time series type of data I thought ...
MLenthusiast's user avatar
0 votes
0 answers
23 views

I'm trying to build image search like Google Photo-Image with face is given to model & it'll get all the images in database in which he/she is present

When a user upload a selfie, the model search same person in dataset of images of multiple persons and get back all the images in which that person is present. Step 1: From dataset of images I detect ...
BKP's user avatar
  • 1
0 votes
0 answers
73 views

Can pretraining be continued after RLHF?

Assume you have a pretrained transformer language model (M1) which already underwent reinforcement learning by human feedback (M2). I assume that it is in principle possible to continue the ...
Hans-Peter Stricker's user avatar
0 votes
0 answers
29 views

Is it possible to combine SGD with an unsupervised learning approach effectively

Before I undertake quite a large project I would like to clarify whether my idea for training a multi-layer neural network will work. I plan to make an AI that can land a rocket from randomly ...
Gamaray's user avatar
0 votes
0 answers
37 views

Is regression method the best for my case?

newbie here. I'm starting to work on a custom model for a very specific task, so I found no pre-trained models for this task so far. After checking (un)supervised learning approaches I believe that ...
Putnik's user avatar
  • 101
0 votes
0 answers
11 views

How to compare word segmentation methods?

I am comparing a few methods of word segmentation in artificial language without dictionary and "golden" segmentation. Let's say, idolikecats is splitted ...
dobrowol's user avatar
0 votes
0 answers
62 views

What is the difference between "Image Clustering" and "Unsupervised Classification" tasks?

I am trying to compare some results that I obtained in benchmarks with my unsupervised model. My model basically takes an unlabelled dataset and clusters it into semantic classes (10 clusters in the ...
puradrogasincortar's user avatar
0 votes
0 answers
35 views

CNN without actuators

After training CNNs without actuators, I have an idea to compare their weights with each other using image mirroring. I am looking for ideas about reality perception of CNNs in this way. What might ...
fkybrd's user avatar
  • 1
0 votes
0 answers
7 views

Surveys, Papers, Hand on Tutorials about training data generation for anomaly detection

I am searching for anything related to supervised, semi supervised or unsupervised anomaly detection w.r.t training data generation. I am looking toward reading any work that tackles the issue how to ...
Skobo Do's user avatar
0 votes
0 answers
83 views

Autoencoder make spectrogram important parts more pronounced with a "log loss"

Hi I want to create a neural network that essentially picks out the most pronounced parts of a spectrogram. Assume this is the True spectrogram: ...
GILO's user avatar
  • 101
0 votes
0 answers
21 views

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 ...
Adrian Evensen's user avatar
0 votes
0 answers
26 views

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 ...
DragonflyRobotics's user avatar
0 votes
1 answer
119 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 ...
user5520049's user avatar
0 votes
1 answer
231 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.
Mika's user avatar
  • 341
0 votes
0 answers
67 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 ...
user3585510's user avatar
0 votes
1 answer
72 views

How can I combine unsupervised learning with supervised learning?

I am currently using an isolation forest (from sklearn library) to detect anomalies in a data frame (basically it's a dynamic data frame more of a kind of time series I am. But I have certain criteria ...
SUNITA GUPTA's user avatar