Questions tagged [learning-algorithms]
For questions about different learning algorithms used by a Machine Learning program to achieve its end goal.
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Best algorithms/approaches for data sets of binary (1/0) features
I am working with a dataset with about 400 features, all binary (1 or 0). What approach would you recommend? Data set is about 500k records.
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What is the borderline between unsupervised learning and regular algorithms?
Unsupervised learning using neural networks is clearly machine learning since it is utilising neural nets.
However, some algorithms, k-means clustering, for example, are considered unsupervised ...
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Can an ML model sort a random sequence of numbers from 1 to $ 2^{2^{512}} $ in our universe in infinite time?
I am pondering on the question in the title. As a human being, somehow I can sort a random sequence of numbers from 1 to $ 2^{2^{512}} $ in our universe in infinite time (But I am not sure.). Can an ...
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Alternatives to Hierarchical RL for centralized control tasks?
Consider a problem where the agent must learn to control a hierarchy of agents acting against another such agent in a competitive environment. The agents on each team need to learn cooperate in order ...
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Can Reinforcement Learning be used for UAV waypoint control?
I want to make a drone which can follow static and dynamic waypoints. I am a total beginner in the drone field so I can't figure out that should I use Reinforcement Learning or any other learning ...
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How do you know if an agent has learnt its environment in reinforcement learning?
I'm new to reinforcement learning and trying to understand it.
If you train an agent using a reinforcement learning algorithm (discrete or continuous) on an environment (real or simulated), then how ...
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Why does the machine learning algorithm need to learn a set of functions in the case of missing data?
I am currently studying the textbook Deep Learning by Goodfellow, Bengio, and Courville. Chapter 5.1 Learning Algorithms says the following:
Classification with missing inputs: Classification ...
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Intellectual property in the age of Industry 4.0
I am looking for specific references describing guidance principles around the interplay between IP (intellectual property) and Artificial Intelligence algorithms. For example, Company A has a large ...
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How can I write out the Real-TIme Recurrent Learning Gradient equations for a network?
This question is about Real-Time Recurrent Learning Gradient on a Recurrent neural network .
How can I write out the RTRL equations for a network ?
Before present an example give let's introduce ...
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How would an AI learn the concept of the words "repeat twice"?
In a hypothetical conversation:
Person A - "Repeat the word 'cat' twice".
Person B - "cat cat".
I'm thinking about how a human or AI can learn the concept of "...
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How can we prove that an autoassociator network will continue to perform if we zero the diagonal elements of a weight matrix?
How can we prove that an auto-associator network will continue to perform if we zero the diagonal elements of a weight matrix that has been determined by the Hebb rule? In other words, suppose that ...
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How do you interpret this learning curve?
Loss is MSE; orange is validation loss, blue training loss. The task is NN regression (18 inputs, 2 outputs), one layer 300 hidden units.
Tuning the lr, mom, l2 regularization parameters this is the ...
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Unable to train Coach for Banana-v0 Gym environment
I have just started playing with Reinforcement learning and starting from the basics I'm trying to figure out how to solve Banana Gym with coach.
Essentially ...
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What is the difference between a learning algorithm and a hypothesis?
What's the distinction between a learning algorithm $A$ and a hypothesis $f$?
I'm looking for a few concrete examples, if possible.
For example, would the decision tree and random forest be considered ...
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Is it possible to do K-nearest-neighbours before training DNN
The following X-shape alternated pattern can be separated quite well and super fast by K-nearest Neighbour algorithm (go to https://ml-playground.com to test it):
However, DNN seems to face great ...
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Algorithm to solve a fault independent of its type
I am looking to plan a solution for a workspace fault and not hardware faults.
Consider a task where a robot has to move balls from one place to another. In case it faces any condition which is ...
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Using ML to analyze Facebook posts
First of all, I should mention that I have a very basic knowledge of ML so I apologize if this question seems trivial or stupid.
I am working on a small personal project, basically an app that ...
user28054
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Use AI to auto-correlate the words of human-translated texts?
There are many, many literary works in the public domain, along with human translations, many of which have entered the public domain as well. (Public domain = easily available)
In order for me to ...
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Can we define the AI singularity mathematically?
The "AI Singularity" or "Technological Singularity" is a vague term that roughly seems to refer to the idea of:
Humans can design algorithms
Humans can improve algorithms
Eventually algorithms we ...
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Does a solution for Wumpus World with neural networks exist?
The Wumpus World proposed in book of Stuart Russel and Peter Norvig, is a game which happens on a 4x4 board and the objective is to grab the gold and avoiding the threats that can kill you. The rules ...
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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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What's an appropriate algorithm for classification with categorical features?
My input data consists of a series of 8 integers. Each integer is a discrete token, rather than a relative numeric value (i.e. '1' and '2' are as distinct as are '1' and '100'). The output is a ...
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Why not teach to a NN not only what is true, but also what is not true?
I'm not a person who studies neural networks, or does anything that is related with that area, but I have seen a couple of seminars, videos (such as 3Blue1Brown's Series), and what I am always told is ...
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Teaching a NN to manipulate pseudoRNG over a long time scale?
For speedrunning purposes, I am trying to train a neural network to identify human-executable ways to manipulate pseudo-RNG (in Pokemon Red, for the interested). The game runs at sixty frames per ...
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Which machine learning algorithm is suitable for detecting text w.r.t set of words
Considering the scenario where supervised training data-set in the form of sentence will be given to train the machine
The Bomb which had been planted by Terrorist on this morning was
defused by ...
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Where do 'random seeds' get used in deep neural networks?
I know that when creating neural networks it's standard practice to create a 'random seed' so that you can get producible results in your models. I have a couple of questions regarding this:
Is the ...
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Which is best: evaluation of states or probability of moves?
If you have a game and you are training an AI there seems to be two ways to do it.
First you take the game-state and a possible move and evaluate whether this move would be good or bad:
(1) ...
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Can we use the recursive least squares as a learning algorithm to an ADALINE?
I'm new to neural network, I study electrical engineering, and I just started working with ADALINEs.
I use Matlab, and in their Documentation they cite :
However, here the LMS (least mean squares) ...
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In the multi-linear regression, how is the value of weight $b_2$ calculated?
In multivariate linear regression (linear regression with more than one variable) the model is $yi = b_0 + b_1x_{1i} + b_2x_{2i} + ...$ , and so on. But how is the $b_n$ value calculated iteratively? ...
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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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Recommend item from set based on features
Forgive what might be a basic question. I'm just experimenting with ML / AL and I have a small problem set and I'd like to see if it can be solved with ML / AI. Basically, given a set of objects ...
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What is the proof behind the gradient of a curve being proportional to the distance between the two co-ordinates in the x-axis?
In the [delta rule][1] the equation to adjust the weight with respect to error is
$$w_{(n+1)}=w_{(n)}-\alpha \times \frac{\partial E}{\partial w}$$
*where $\alpha$ is the learning rate and $E$ is the ...
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How do stacked denoising autoencoders work
I've been studying a recommender system which uses a collaborative deep learning approach and Bayesian learning. It has the following NN representation :
I need to know the working of stacked ...
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Natural language processing with a continuous dependent variable
I have a large number of observations. Each observation contains:
dependent variable: a scores ranging from 0 - 100
independent variable: a large article
I want to know which words or phrases ...
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Trading off "Memory" vs "Optimization"
I've been researching the following topic. Or rather, I would like to but I can't find anything because I'm not sure what to look for.
I am interested weather there are some concepts or models that ...
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Machine learning algorithm for xml manipulation [closed]
Given a virtual game map (picture) and a racing car at the map's starting point, I'm trying to build an algorithm that would help me generate a route that would get the car from the beginning to the ...
user9890
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Approaches to an algorithm for crossing a road
I want to write an algorithm which indicates to a robot the first point in time when it is reasonably safe to cross a road. Assume that the robot's goal is to travel to a location that requires a ...
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Is a decision tree less suitable for incremental learning than e.g. a neural net?
I can recall that a professor once said that decision trees are not good for incremental learning, as they have to be rebuilt from the ground up if new training examples arrive.
Is this basically ...
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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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How can artificial intelligence (including deep learning algorithms) find suspicious patterns in the body’s biochemistry?
It has been suggested that machine learning algorithms (also Watson) can help with finding disease in patient images and optimize scans. Also that deep learning algorithms show promise for every type ...
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Which learning algorithms are suitable for data leakage detection and prevention?
I'm investigating applications of AI algorithms which can be used for data leakage detection and prevention within an intranet network (like Forcepoint). More specifically detecting traffic patterns. ...
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