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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.

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10
votes
5answers
13k views

Using Machine/Deep learning for guessing Pseudo Random generator

Is it possible to feed a neural network, the output from a random number generator and expect it learn the hashing/generator function. So that it can predict what will be the next generated number? ...
8
votes
5answers
4k views

Which machine learning algorithm can be used for pattern recognition?

I need a machine learning algorithm to identify any patterns in a CSV file, which contains details of a cache performance of a CPU workload. More specifically, the CSV file contains columns like ...
6
votes
1answer
811 views

Is the new Alpha Go implementation using Generative Adversarial Networks?

I read through the publication Mastering the game of Go without Human Knowledge. It doesn't seem to use GANs, just a new form of search and reinforcement learning.
6
votes
3answers
255 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 - "...
6
votes
2answers
2k views

What is the difference between assisted and unassisted learning in relation to AI?

Is this related to supervised and unsupervised machine learning? Is it related to AI assisted human learning, and what is the distinction? Also, why is assisted machine learning seen as an ...
5
votes
1answer
205 views

What is the calcium equivalent role in neural networks

I understand that neural networks model biological neurons. Each node in the network represents a neuron cell and the connections between nodes represent the connections between cells. As in nature, ...
5
votes
3answers
214 views

Why do Decision Tree Learning Algorithm preferably outputs the smallest Decision Tree?

I have been following the ML course by Tom Mitchel. The inherent assumption while using Decision Tree Learning Algo is: The algo. preferably chooses a Decision Tree which is the smallest. Why is ...
5
votes
1answer
309 views

Learning algorithms of 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 ...
5
votes
2answers
445 views

Do GAN's come under Supervised Learning or Unsupervised Learning?

My guess is that they come under supervised learning, as we have labelled dataset of images, but I am not sure as there maybe other aspects in GANs which might come into play in the determination of ...
5
votes
1answer
476 views

What makes learned feature detectors specialize in CNN?

It has been shown that it is possible to use unsupervised learning techniques to produce good feature detectors in CNNs. I can't understand what drives specialization of those feature detectors. In ...
4
votes
2answers
115 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 ...
4
votes
1answer
98 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 ...
4
votes
3answers
548 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
votes
2answers
474 views

At what rate could AI theoretically self-improve?

Due to recursive self-improvement, AI could lead to an intelligence explosion improving on itself year over year exponentially. Assuming the proper environment was created to allow an AI to self-...
4
votes
2answers
61 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 ...
4
votes
1answer
236 views

Unsupervised alien natural language learning

While conducting research, I recently stumbled upon the deep learning and natural language processing concepts. In this question they say that the ‘grammar induction’ is a ‘supervised learning’ mode. ...
4
votes
1answer
46 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. ...
3
votes
2answers
267 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 ...
3
votes
1answer
30 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., ...
3
votes
1answer
457 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?
3
votes
1answer
108 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 ...
3
votes
2answers
73 views

Learning in unsupervised learning

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
votes
2answers
138 views

Predict frequently purchased items under certain conditions with customer purchasing history data

I have purchasing history data for grocery shopping. I am trying to get abnormally frequently purchased items under certain conditions. For instance, I am trying to find frequently purchased items, ...
3
votes
1answer
324 views

Which Reinforcement Learning algorithms are efficient for episodic problems?

I have some episodic datasets extracted from a turn-based RTS game in which the current actions leading to the next state doesn’t determine the final solution/outcome of the episode. The learning is ...
3
votes
0answers
30 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 ...
3
votes
3answers
400 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 ...
2
votes
1answer
470 views

How does an unsupervised learning model learn?

How does an unsupervised learning model learn, if it does not involve any target values?
2
votes
2answers
84 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 ...
2
votes
1answer
80 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 ...
2
votes
1answer
204 views

Does eligibility traces and epsilon-greedy do the same task in different ways?

I understand that in Reinforcement Learning algorithms such as q-learning, to prevent selecting the actions with greatest q-values too fast and allow for exploration, we use eligibility traces. Here ...
2
votes
2answers
76 views

Will artificial super-intelligence evolve to have selfishness inherent in biological systems?

A lot of experts have expressed concerns about evil super intelligence. While their concerns are valid, is it necessary, what are the chances or how the artificial super-intelligence will evolve to ...
2
votes
1answer
44 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 <...
2
votes
1answer
43 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 ...
2
votes
1answer
31 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 ...
2
votes
2answers
62 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, ...
2
votes
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 ...
2
votes
1answer
143 views

Keras pattern finding between hash and word

My goal is to build a neural net that can find patterns between a hash and a word on it's own. So that it returns the word of any hash that I will input. Unfortunatally my skill in the area of ...
2
votes
1answer
55 views

Is it possible for 'unsupervised learning' model to recognize features on unlabelled images?

Is it possible for unsupervised learning to learn about high-level, class-specific features given only unlabelled images? For example detecting human or animal faces? If so, how?
2
votes
0answers
24 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
votes
1answer
44 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 ...
1
vote
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. ...
1
vote
1answer
357 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 ...
1
vote
1answer
31 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 ...
1
vote
1answer
28 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 ...
1
vote
0answers
37 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? ...
1
vote
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-...
1
vote
0answers
50 views

AUTOENCODERS FOR CREDIT CARD FRUD DETECTION

Am working on credit card fraud detection problem using autoencoders. Regarding that I have some doubts given below : The dataset for the above problem has been downloaded from kaggle which is highly ...
1
vote
0answers
28 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 ...
1
vote
1answer
130 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-...
1
vote
0answers
56 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 ...