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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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Deep apply to patient clustering

I'm currently doing a computer engineer internship in the field of artificial intelligence. I would like you to criticize my work. Also I have more specific questions that I will put at the end of ...
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1answer
20 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
20 views

What are some limitations of using Collaborative Deep learning for Recommender systems?

Recently I worked on a paper by Hao Wang- Collaborative Deep learning for Recommender Systems which uses a two way tightly coupled method, Collaborative filtering for Item correlation and Stacked ...
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1answer
23 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
52 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 ...
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0answers
10 views

Python clustering implementation for mix of categorical and numerical variables

Are there any Python implementations for clustering tasks which include data of both categorical and numerical nature? I could not find anything except for the Gower's distance which seems to work ...
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1answer
31 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 ...
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1answer
252 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 ...
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2answers
50 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 ...
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23 views

Building a VAE architecture to reconstruct images

I am trying to build a VAE architecture in Lasagne which is able to reconstruct MNIST images. Note that I want to be able to sample from both the encoder and the decoder. So far, my architecture is ...
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1answer
100 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
64 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
124 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
232 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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25 views

Detecting patterns in Dataset containing DB columns

How do I detect patterns in dataset containing database columns extracted from Oracle or SAS database, which R machine learning algorithms should be used for the same and from where i can get sample ...
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0answers
36 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 ...
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2answers
55 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 ...
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2answers
177 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 ...
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1answer
56 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 ...
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2answers
104 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, ...
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1answer
112 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 ...
3
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1answer
93 views

K-Armed Bandit and Reinforcement Learning

In the book "Reinforcement learning" by Sutton there is a discussion of the k-armed bandit problem, where the expected reward from the bandits changes slightly over time (is non-stationary). Instead ...
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1answer
304 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-...
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1answer
213 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 ...
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0answers
23 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 ...
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1answer
61 views

How does this part of algorithm works?(K-means)

I can't understand the red box. what do does that 1 do before {c(I)=j} ? Also how does all the algorithms work? May someone ...
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1answer
579 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.
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1answer
152 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 ...
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1answer
247 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 ...
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5answers
6k 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? ...
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2answers
1k 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 ...
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3answers
142 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 ...
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1answer
206 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. ...
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1answer
271 views

Neuro-evolution: Is it not Supervised Learning?

If I compare back-propagation to feed-forward neuro-modulation, the latter is unsupervised in that it requires no labeled data set. Applying to it a genetic algorithm to refine topology and weights, ...
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2answers
72 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 ...
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1answer
189 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, ...
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1answer
51 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?
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1answer
300 views

How does unsupervised learning model learn?

Unsupervised learning does not involve target values, so basically targets are most likely the same as the inputs (in other words, involves no target values). So how does this model learn?
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3answers
56 views

AIs' self-evaluation threshold

Is it possible that at some time in the future, AIs will be able to initiatively develop themselves, rather than passively being developed by humanity?
3
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1answer
339 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?