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.
2
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2answers
36 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, ...
0
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1answer
29 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 also known as an unsupervised neural network. I plan on doing this in Python in order to better understand how it works. ...
0
votes
0answers
13 views
Visualizing Clusters in Self Organizing Map
I am a bit confused about how can i visualize clusters in a Self Organizing Map. The input data is a set of images, where each image is an english alphabet in some font. Now if i have to visualize the ...
0
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0answers
19 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 ...
0
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0answers
11 views
How to remove unwanted signals from the sensor measurement?
I have 2 tabular datasets, one is clean and one is drifted.
They are records of sensor measurements. I move the sensor around in the room and collected thousands of measurements.
I have a sensor that ...
3
votes
3answers
141 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 ...
1
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0answers
19 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
25 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
24 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 ...
0
votes
1answer
29 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 ...
0
votes
1answer
28 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 ...
5
votes
2answers
198 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 ...
0
votes
1answer
32 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 ...
5
votes
1answer
260 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 ...
4
votes
2answers
57 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
vote
1answer
108 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
2answers
68 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. ...
3
votes
2answers
181 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 ...
6
votes
3answers
237 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 - "...
1
vote
0answers
45 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
votes
2answers
60 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 ...
5
votes
2answers
320 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 ...
3
votes
1answer
58 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 ...
4
votes
2answers
124 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, ...
2
votes
1answer
118 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
votes
1answer
99 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 ...
4
votes
2answers
404 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-...
3
votes
1answer
276 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 ...
1
vote
0answers
25 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 ...
1
vote
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 ...
6
votes
1answer
681 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.
2
votes
1answer
167 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 ...
5
votes
1answer
376 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 ...
8
votes
5answers
9k 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? ...
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
3answers
184 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 ...
4
votes
1answer
217 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. ...
1
vote
1answer
309 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, ...
2
votes
2answers
74 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 ...
5
votes
1answer
198 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, ...
2
votes
1answer
53 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?
1
vote
1answer
356 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?
1
vote
3answers
65 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
votes
1answer
407 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?
