Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.

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6 views

How to choose normalizing factor in regret matching algorithm

How to choose the normalizing factor for the max regret calculated in the regret matching algorithm? Generally the normalizing factor is the time 'T' but in my case, the utility function values vary ...
3
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1answer
33 views

Genetic Algorithm, Neural Network, Deep Learning, Machine Learning Similarities and Applications? [on hold]

I am a computer engineering student and trying to get the idea behind all these Artificial Intelligence Concepts and applications. I know little theoretically about machine learning and some high ...
2
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0answers
17 views

ANN - Backpropagation with multiple output neurons

Can I utilize the backpropagation algorithm in a layered, feed-forward ANN in instances where there are multiple output neurons? If so, how? Links to (somewhat) comprehensible resources would be ...
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1answer
25 views

what is the general name of this problem?

what is the general name of a problems where learning agent observe new data as a learning goes on. For example when playing platformer games one must incrementally learn new level areas and states ...
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0answers
30 views

Formula for number of parameters in an undirected graphical (probability) model

I have googled endlessly, and I cannot find it. Can anyone point me to a reference that gives a way to calculate the number of parameters in an undirected Graphical Model? Adapting from the similar ...
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0answers
9 views

how binary quantile regression divides the dependent variable into quantiles

I am not very clear with binary quantile regression. As if it was ordinary quantile regression, it would divide the dependent variable's value by its ascending value into quantiles. But I cannot ...
3
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0answers
52 views

Prerequisites for AI and machine learning [closed]

I am interested in the field of AI and machine learning and I am fairly good at mathematics and statistics and programming in general. However I lack a formal CS education and my undergraduate degree ...
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0answers
13 views

Random Forest closed loop

I'm using the Random Forest algorithm for classification. I have some variable to use as features in input, but I was wondering if I can use the output of the classification itself as input. Suppose, ...
2
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1answer
28 views

Feature values range

Suppose I am about to use SVM for learning a classification or ranking function. Suppose that my feature vectors are two dimensional and that values for one dimension are, say, natural numbers and the ...
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0answers
16 views

recommender system using SVD

I have followed the following steps listed in any introductory text,on how to do matrix factorisation using SVD on the Movielens dataset. replace all zero entries with mean rating of the movie(some ...
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0answers
37 views

Learn feature value range for a classification

Which domain does this problem belong to? Given a set of products some are classified as cheap and some not. The task is to determine the price range (probabilistic) for cheap products. Supervised ...
1
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1answer
28 views

Similarity based document classification compared to the user profile ratings

I need to understand a distinction to check if I understood a document classification problem right. Given a training set of documents with ratings, that a user has given, let's say rating $r_{k} \in ...
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0answers
10 views

Simple Good-Turing smoothing algorithm question [migrated]

I was reading this program written by Sampson (one of the guys from Good-Turing smoothing without tears*): http://www.grsampson.net/D_SGT.c And I was having trouble understanding the process to get ...
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0answers
13 views

How does SARSA handle episode termination

When applied to domains that are episodic and have a "final" state but no final action, like a game, how does SARSA update the Q-values? e.g. A game agent would receive this series: ...
4
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2answers
66 views

Why is the O(nW) algorithm for the Knapsack problem not a polynomial one?

On the wikipedia page for the knapsack problem it says that the runtime is $\mathcal{O} (nW)$ and goes on to say that this doesn't violate its classification as NP because the input size is related to ...
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0answers
27 views

Merging two disconnected graphs

Firstly, I'd like to apologize for any misused terms or ways I could have made the description much more succinct. It's been a while since I took machine learning during my bachelor's. I have two ...
1
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0answers
13 views

How to make logical inference from simulated data

I have data collected from a computer simulation of football games which seem to have recurring patterns of the following form. if madrid plays arsernal and the match ends under 3 goal, then on ...
2
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1answer
23 views

What's the difference between Adaptive Control and Hierarchical Reinforcement Learning?

After watching Travis DeWolf presentation on scaling neural computation, I'm a bit confused about the difference between Reinforcement Learning (whether hierarchical or not) and Adaptive Control. They ...
3
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0answers
20 views

What's the difference between adaptive control and a kalman filter?

From my basic understanding of Adaptive Control, I understand that it uses the error and the velocity of the error to approximate the error in the solution space of a problem, thus allowing for ...
2
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0answers
23 views

Training a model to match two time series

Context I have two related time series, I want to learn to produce one from the other. However, they aren't synchronous, and the lag between the two does not revert to the mean, it accumulates. ...
2
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1answer
41 views

I am having trouble understanding (and implementing) logistic regression for classifying into three classes

(For reference, i am using Kevin P Murphy's Book "Machine Learning: A Probabilistic Perspective" and implementing with MATLAN - without any toolboxes) I have a dataset with 392 samples (rows), each ...
1
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0answers
20 views

backpropagation algorithm seems to be forcing output values to middle than extremes

I have been playing around with artificial neural networks lately, specifically with the prospect of trying to replace the contrastive divergence algorithm with some type of evolutionary metaheuristic ...
3
votes
1answer
80 views

How does the momentum term for backpropagation algorithm work?

When updating the weights of a neural network using the backpropagation algorithm with a momentum term, should the learning rate be applied to the momentum term as well? Most of the information I ...
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0answers
16 views

Is this an accepted/valid clustering evaluation metric?

We have a clustering algorithm where the number of clusters isn't known to the algorithm - it iteratively creates clusters out of similar-looking data points. The evaluation metric we're currently ...
5
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1answer
61 views

How exactly do you calculate the hidden layer gradients in the backpropagation algorithm?

I have been going through the description of the backpropagation algorithm found here. and I am having a bit of trouble getting my head around some of the linear algebra. Say I have a final output ...
1
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1answer
27 views

are the activations of hidden nodes in an ANN binary or real valued?

this may seem to be a pretty basic question, but it is something i have been puzzling over for some time. when calculating the activations of nodes in a hidden layer in an ANN using sigmoid neurons ...
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2answers
73 views

Which type of randomized algorithm is best suited for web crawling?

I have decided to implement a web crawler for my CS major project. The project is focused towards adaptive search. I want the pages to be as user specific as possible and time efficiency is not much a ...
2
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1answer
66 views

In ID3 algorithm, which attribute to choose if information gains are equal?

In the ID3 algorithm for building a decision tree, you pick which attribute to branch off on by calculating the information gain. What happens if the calculated information gain is equal for two ...
2
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0answers
24 views

Reinforcement learning - state space and action space

I am working on a reinforcement learning strategy for parameter control of a local search heuristic. The complete state for this RL problem can be defined as $S = \{s, p\}$, where $s$ and $p$ ...
2
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2answers
77 views

Combining multiple HMM models

Is there any way to combine multiple Hidden Markov Models trained from different sets of data? For example, I want to detect the phases of a sequential activity. I collect two sets of data by using ...
0
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1answer
54 views

Find pixel mapping matrix with minimum iterations

The Situation I am an electronics engineer and on a volunteer team that have built a prototype eye that has 200*200 sensors that are mapped to the optic nerve, the connection to the optic nerve is ...
3
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2answers
50 views

How do I measure the reliability of a confidence value in a predictive algorithm?

Supposing I have some algorithm that is able to provide me with a confidence value for some event occurring. Let's say on day 1 it tells me that there is a 80% chance it will rain, on day 2 it tells ...
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0answers
25 views

How to discern devices based on their traces?

I would greatly appreciate your advice on following machine learning problem: I need to train a classifier to learn a device's behavior. The device itself can be observed under different ...
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0answers
19 views

What math is required for machine learning, neural networks etc.? [duplicate]

I'm planning to start learning more in depth about neural networks and machine learning. Can someone tell me which math will I need the most, and also recommend me good books or internet lessons in ...
6
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2answers
104 views

Are there ways to automatically (no human testing) measure a $9 \times 9$ Sudoku puzzle's average hardness for a human to solve?

So most resources providing Sudoku puzzles assign a difficulty category to each puzzle, even some I've seen with 15 or more difficulty categories. But what is a good way to assign these difficulty ...
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0answers
64 views

Improving MSE as fitness function for a genetic algorithm

I am implementing an autoencoder neural network in matlab, the weights of which are being optimised by a genetic algorithm. At the moment I am working on the first layer, trying to get an improved ...
1
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0answers
44 views

Disadvantages to using simple step functions for activation in neural networks?

From what I have read, the main advantage to using tanh(x) or sigmoid(x) as an activation function for neural networks is that it is very easily differentiable. I am trying to implement a neural ...
0
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1answer
68 views

How to reconstruct the image from a neural network output?

I am trying to use the genetic algorithm to optimise a multi-layered neural network for image classification (i am using a subset of the MNIST handwritten digit data set as my initial dataset, but ...
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0answers
29 views

Detect bad acceleration deceleration of car [closed]

I am working on aggressive driving behavior android application. This will be implemented via supervised learning, wrong actions will be recognized and added while driving the car. To check ...
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0answers
44 views

Sample Complexity for Real-Valued PAC-Learnable Functions

Can anyone shed some light on how the VC Dimension affects the sample complexity bounds of infinite hypothesis classes with real-valued outputs in PAC learning, or how to calculate the sample ...
3
votes
1answer
58 views

How can we combine badly trained decision trees to a good one?

I was reading about decision trees and this is what I understood: We build decision trees by choosing an attribute and building subtrees (which are also decision trees) as children of the node ...
2
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5answers
202 views

Machine Learning and Neural Networks for High School Students

I hope this question is appropriate for this forum. In this summer I am giving a 3-day workshop on machine learning and neural networks for advanced and very enthusiastic high school students which ...
0
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0answers
50 views

Activity prediction in a kitchen

Here is the scenario: There are three chefs(A- main chef, B and C- assistant) working together to prepare a diner set. The sequence of the event is as following. Start: The three chefs enter the ...
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0answers
14 views

What are Pairwise intensity comparison in binary image descriptors?

Recently many binary descriptors have come u like BRIEF, ORB etc. A common ste in such descriptors is to chose a sampling pattern and perform pairwise intensity comparisons for constructing the binary ...
2
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3answers
148 views

Does programming language detection need more input than natural language detection?

I wonder which one of the two needs a larger input to achieve a decent accuracy: programming language detection or natural language detection? More details: Definition of Language detection: ...
2
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1answer
45 views

Closed form solution for a single layer linear perceptron

Let f be a one-layer neural network which is linear (ie. no activation function). Let it have $p$ inputs and $q$ outputs. These are fully connected by weights $W$. We have $n$ inputs $x \in ...
1
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0answers
17 views

Baseline approaches for likes prediction

I have a small user-item matrix (25k x 1.8k) describing how users liked or disliked some of the items. Users don't have any attributes but items have several features. I would like to be able to ...
2
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1answer
48 views

Generative Machine Learning algorithms on tree structure

I'm looking into PCFG sentence grammar dependency structure parsing using StanfordNLP PCFG parser. It generates tree structures represented as a string like this: ...
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0answers
49 views

Where to start studying about HTM?

I am looking for references (pedagogic and beginner friendly!) to these two topics, hierarchical temporal memory algorithms applied to deep planning problems (multi-layer) neural networks trained ...
2
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0answers
46 views

Two classes of documents. Find weighted relations between them

I have an NLP problem and a potential solution, but I’m a bit green here, so I’m looking for some validation or alternative suggestions. Background I have two types of documents: one is a set of ...