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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3answers
753 views

How to implement a Continuous Control of a quadruped robot with Deep Reinforcement Learning in Pybullet and OpenAI Gym?

Description I have designed this robot in URDF format and its environment in pybullet. Each leg has a minimum and maximum value of movement. What reinforcement algorithm will be best to create a ...
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0answers
28 views

State values in Deep Reinforcment Learning [closed]

I am learning deep reinforcement learning. I'm a bit confused in state values. Is it possible to use dynamic values in states or do we have to use discrete values and create a state for each value we ...
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2answers
39 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 ...
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1answer
28 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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0answers
11 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 \...
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1answer
27 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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2answers
99 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
21 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
25 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
206 views

Dense bottleneck layer in Autoencoder

I would like to use the bottleneck layer of U-Net (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 my ...
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1answer
32 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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48 views
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6answers
64 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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2answers
45 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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2answers
508 views

Why does unsupervised pre-training help in deep learning?

What is the effectiveness of pre-training of unsupervised deep learning? Does unsupervised deep learning actually work?
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5answers
7k views

Which machine learning algorithm can be used to identify patterns in a dataset of the cache performance of a CPU?

I need a machine learning algorithm to identify patterns in a dataset (saved in a CSV file) that contains details of the cache performance of a CPU. More specifically, the dataset contains columns ...
2
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1answer
30 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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1answer
28 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 ...
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1answer
49 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 ...
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1answer
142 views

Kohonen clustering of flowers

I have a question about output of my SOM network. I have trained my network with diffrent size, learning rate and epochs, but my output always can recognise two big clusters. Iris-setosa and Iris-...
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1answer
32 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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2answers
999 views

Do GANs come under supervised learning or unsupervised learning?

Do GANs come under supervised learning or unsupervised learning? My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other ...
1
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1answer
31 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 ...
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0answers
29 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 ...
2
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1answer
69 views

Reconstruction Errors in Auto Encoders after Training

Autoencoders are used for unsupervised anomaly detection by at first learning the features of the data set with mainly "normal" data points. Then new data can be considered anomalous, if the new data ...
4
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1answer
59 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. ...
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0answers
41 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?
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3answers
674 views

Is it possible to write an adaptive parser?

I am working on a js library which focuses on error handling. A part of the lib is a stack parser which I'd like to work in most of the environments. The hard part that there is no standard way to ...
4
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1answer
42 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 ...
2
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1answer
103 views

Why isn't the Credit Card Fraud Detection dataset from Kaggle already balanced?

I am working on a credit card fraud detection problem using autoencoders. I have a question regarding the dataset I'll be using. I've downloaded the dataset for the above problem from Kaggle, which ...
6
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2answers
324 views

What are different approaches used in Machine Learning?

There seem to be so many sub-fields, so I'm interested in getting a better understanding of the approaches. I'm looking for information on a single framework per answer, in order to allow for ...
3
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1answer
59 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 ...
7
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1answer
379 views

What is the relationship between these two taxonomies for machine learning with neural networks?

Could you please let me know which of the following classification of Neural Network's learning algorithm is correct? The first one classifies it into: supervised, unsupervised and reinforcement ...
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2answers
242 views

Where can I find an implementation of the wake-sleep algorithm?

I'm looking to build from scratch an implementation of the wake-sleep algorithm, for unsupervised learning with neural networks. I plan on doing this in Python in order to better understand how it ...
3
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2answers
98 views

Why do we need learning in unsupervised learning? [duplicate]

I am not clear with the concept that an unsupervised model learns. We are giving an input and output to the supervised model, so that it can generate a particular value, pattern or something out of it ...
3
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1answer
111 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 ...
3
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1answer
80 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 ...
5
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2answers
404 views

How can a neural network work with continuous time?

I have an ANN model that receives an input and produces an output. The output is an action that interacts with the environment and changes the input accordingly. The network has a desired environment ...
4
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2answers
159 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 ...
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0answers
89 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? ...
3
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1answer
34 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., ...
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2answers
100 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 ...
3
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1answer
61 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 ...
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1answer
90 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 ...
2
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1answer
41 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 ...
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1answer
378 views

Does neuroevolution require a labelled dataset?

A neuroevolution algorithm, such as DXNN, can be used to refine the topology and weights of an artificial neural network (ANN). The GA will require a fitness function, which means you need labeled ...
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0answers
13 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 ...
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0answers
20 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 ...
3
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1answer
507 views

How does an unsupervised learning model learn?

How does an unsupervised learning model learn, if it does not involve any target values?
3
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1answer
53 views

Which unsupervised learning algorithm can be used for peaks detection?

So, I have a dataset which has around 1388 unique products and I have to do unsupervised learning on them in order to find anomalies (high/low peaks). The data below just represents one product. The <...