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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26 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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1answer
31 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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1answer
29 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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28 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
39 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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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 ...
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1answer
24 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
76 views

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

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 ...
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1answer
77 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 ...
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1answer
41 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 ...
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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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1answer
32 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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70 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? ...
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2answers
98 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 ...
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1answer
25 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 ...
3
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1answer
59 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
77 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 ...
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1answer
38 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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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
182 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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0answers
18 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 ...
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1answer
65 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 ...
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2answers
139 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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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 <...
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0answers
32 views

References and books for unsupervised learning

I am looking for good introductory and advanced books in AI, especially unsupervised learning. I have already read books like Probabilistic Graphical Models from D. Kholler and Pattern Recognition and ...
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0answers
41 views

Unsupervised LSTM

I have a big amount of light curves (image below) and I am trying to label the points as signal or background (the signal appears usually periodically, several times, for a given light curve). However,...
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1answer
458 views

Variational Autoencoder task for better feature extraction

I have a CNN with the regression task of a single scalar. I was wondering if an additional task of reconstructing the image (used for learning visual concepts), seen in a DeepMind presentation with ...
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0answers
14 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-...
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1answer
113 views

Unsupervised Learning for anomaly detection

I've started working on anomaly detection in Python. My dataset is a time series one. The data is being collected by some sensors which record and collect data on semiconductor making machines. My ...
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1answer
84 views

What is graph clustering?

There are several (family of) algorithms that can be used to cluster a set of $d$-dimensional points: for example, k-means, k-medoids, hierarchical clustering (agglomerative or divisive). What is ...
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2answers
69 views

Which unsupervised anomaly detection algorithms are there?

I need to create model which will find suspicious entries or anomalies in a network, whose characteristics or features are the asset_id, ...
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2answers
194 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 ...
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0answers
29 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 ...
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3answers
671 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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1answer
97 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 ...
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0answers
29 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 ...
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1answer
33 views

Steps for final Logistic Regression Modal

I am new for machine learning and I am tried to understand basic steps to get final modal of Logistic Regression. I know Logistic Regression is supervisory learning technique. Therefore we want to ...
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1answer
62 views

Using unsupervised learning for classification problems

Let's say there are two types of cancer(Type 1 and Type 2). Say we want to see if one of pour friends has cancer Type 1 or 2. We can treat this as a classification problem. But what if we use ...
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2answers
807 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 ...
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1answer
36 views

What is the approach to deduce formal rules based on data?

We have data in text format as sentences. The goal is to detect rules which exist in this set of sentences. I have a limited set of contextless sentences that fit a pattern and want to find the ...
7
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1answer
376 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
64 views

What techniques to explore for dynamic clustering of documents (emails)?

I have a dataset of unlabelled emails that fall into distinct categories (around a dozen). I want to be able to classify them along with new ones to come in the future in a dynamic matter. I know that ...
1
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1answer
141 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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2answers
75 views

Classifying non-labeled data with high dimensionality

Disclaimer: I am a novice in the world of machine learning, so please excuse my ignorance. My dataset consists of things like age, days since last visit, etc. This information is medical related. ...
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2answers
285 views

Can agent based machine learning achieved with any ML algorithms other than neural network?

I would like to know other tha neural network, is there any ML technique for agent based ML. If so how to train an agent with some predefined rules? Can we use python programming for representing ...
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3answers
263 views

Has anybody tried unsupervised deep learning from youtube videos?

YouTube has a huge amount of videos, many of which also containing various spoken languages. This would presumably provide something like the data that a "challenged" baby would experience - "...
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0answers
60 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 ...
3
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2answers
97 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 ...
6
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3answers
659 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 ...
2
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1answer
60 views

Detect observations under certain conditions

I have a customer purchasing dataset and the data set is from a retailer having an online store and offline stores. So, customers have two options in their shopping channel, online or offline. In an ...