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

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Automatic Speech Recognition (ASR)

I want to build a Automatic Speech Recognition (ASR) engine for myself, but I've no idea from where to start. I've read that most ASR's are build upon Hidden Markov Models, but also I've read that ...
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8 views

Amplifying a Locality Sensitive Hash

I'm trying to build a cosine locality sensitive hash so I can find candidate similar pairs of items without having to compare every possible pair. I have it basically working, but most of the pairs in ...
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1answer
24 views

Why is the most probable assignment for all variables in MRFs called MAP assignment?

I am new to graphical model, especially Markov Random Fields. I have a question about MAP assignment. Let say we have the graph structure and all the potential functions. MAP assignment in MRFs is ...
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71 views

Who coined the term “machine learning”?

I'm trying to figure out who coined the term "machine learning". An ancillary question is from where is Arthur Samuel cited as defining the field of "machine learning" in 1959 as: the field of ...
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29 views

where should I begin : I need to predict power consumption of a household?

I have the power consumption values of a household for 2 year. To preserve privacy I am down sampling this data before sending it to the utility company. My goal is to get back the original data from ...
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1answer
8 views

Adding concept drift to data sets

I'm about to work with concept drift problem in data streams. I need to start with real data sets from UCI machine learning repository and add to them concept drift (in attributes domain). Do you ...
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2answers
43 views

Learning Quadratic Functions

I have seen in some ML tutorial that functions of the form $f(\vec x) = \vec x^T A \vec x$ ($\vec x \in \mathbb{R}^n$ and $A$ is an $n\times n$ real matrix) can be PAC learned. Can anyone point me ...
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0answers
16 views

Ridge regression with more small errors

I've been using kernel ridge regression. My problem requires predicting some values which I know to be integers. By rounding the results to the nearest decimal, I get excellent results. However, If ...
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1answer
45 views

Cognitive Computing vs Artificial Intelligence?

Can anyone please tell me the difference between them? A brief definition of Cognitive Computing would appreciated. Also how does cognitive computing relate to neural networks? Thank you~
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28 views

How regression is used in item-based collaborative filtering?

In the paper "Item-Based Collaborative Filtering Recommendation Algorithms" In section 3.2.2 about regression, it is said the the user's actual rating of item N (Ru,n), is replaced with an estimate ...
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1answer
31 views

How does the ID3 Algorithm differ from a generic Decision Tree learning algorithm

Based on the notes of my Machine Learning lecturer, I am struggling to understand how the two algorithms differ? Both seem to select the most informative feature A (based on least entropy), then ...
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24 views

Is a KNN-Classifier memory intensive?

In my opinion it seems fairly obvious that a $k$ nearest neighbours (KNN) Classifier would be fairly expensive in terms of memory, as the model is the training set itself. However, any notes I've read ...
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23 views

Learning Hierachial representation of objects in a unsupervised manner

I am trying to understand how the how a hierarchal representation of an object can be learned in a unsupervised manner, using the method described in this paper. ...
3
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1answer
78 views

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

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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2answers
64 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
32 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
36 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
11 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
58 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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17 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
30 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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18 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
44 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 ...
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0answers
35 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
15 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: ...
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2answers
73 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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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 ...
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16 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 ...
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1answer
31 views

How to identify statistically distinct features of different sets?

I have two non-overlapping sets of items, with feature counts for each. What standard algorithms can I use to extract the most statistically distinct features of each set? For example: Items served ...
2
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1answer
27 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 ...
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0answers
27 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
27 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
48 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 ...
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0answers
23 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
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1answer
169 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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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
71 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 ...
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1answer
28 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
80 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
83 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
25 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
145 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
56 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
56 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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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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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 ...
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2answers
109 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
70 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 ...
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0answers
50 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
73 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 ...