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

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15 views

What is linear relaxation in the context of bayesian networks?

To add onto the question, how are elliptical differential equations applicable in this context? I was listening to a talk about Bayesian networks and someone asked if they were using differential ...
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2answers
44 views

Can a self-learning appliance be developed?

I have heard of machine learning systems that can learn from trials of data what effect it should have, but I was wondering is it possible to make a learning appliance that builds on past data? ...
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0answers
26 views

How i can find novel machine learning algorithms? [on hold]

Is there any machine learning algorithm from 2010 to now for classification that is useful and popular.I want to use this learning algorithm for pattern classification. I need a novel method with high ...
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1answer
14 views

Main difference between data mining and statistics? [on hold]

Still don´t get the differece between data mining, machine learning, KDD with statistics. I´m making my thesis for my bachelor degree on computer science as theoretical framework i need to define ...
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0answers
14 views

I need a textbook for machine learning with programming approach [closed]

I'm taking an online course of machine learning, and I need a good textbook in machine learning better to be with MATLAB applications.
2
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2answers
96 views

EM algorithm for two Gaussian models

This is about basic machine learning which I do not understand clearly. I have 2 Gaussian models $G_1$ and $G_2$ and given a list of data as below. (1, 3, 4, 5, 7, 8, 9, 13, 14, 15, 16, 18, 23) I ...
2
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0answers
21 views

Document clustering for summarization

I am curious as to what steps one would reasonably need to take to perform an extraction-based text summarizer. I've taken a look at some papers I've found on Google such as this one, which explains ...
2
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1answer
74 views

Method to recognize abstract objects such as hand-drawn objects?

My research is in the area of Document Image Analysis. To be specific, the topic of my thesis is to automatically recognize and index characters in a set of hand-drawn objects, e.g. given a volume of ...
1
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2answers
54 views

Perceptron learning rule doesn't work [closed]

i'm a little bit lost ... can you help me ? So I have this table of date (each row give a point with its group) So i took a random weight let's say : [1, -2] H = 1 if n =< 0 0 otherwise ...
5
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2answers
92 views

Unknown notation “$e^T$” in a machine learning paper

I'm trying to understand the material in "A Dual Coordinate Descent Method for Large-scale Linear SVM" by Hsieh et. al. (link to paper) There is an equation for the Dual form of an unconstrained ...
0
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0answers
30 views

Haar cascade vs Lbp cascade vs Hog Cascade in object detection

I am doing an project about recognizing one kind of leaf. Well I am using Emgucv with visual stduio 2010 c#. I have read about using 3 differente features extraction but I do not know when I can use ...
0
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1answer
20 views

Clustering a matrix into similar groups

I'm working on a problem where I have a matrix of values which I know will be in groups of similarly-valued elements. I am trying to find these groups of similarly-valued elements. I'm going to ...
1
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1answer
51 views

What are good counter-examples when training an apple classifier?

I am doing a project in order to recognize an apple. (I am using Emgucv with Visual Studio 2010 C#, if that's relevant). My project is a classification (is or is not an apple). I have 2000 images of ...
2
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0answers
24 views

Advantages of adaboost over gentleboost in applications, or vice versa?

I've been researching on AdaBoost and GentleBoost classifiers, but can't seem to find a clear answer to the question: What is Adaboost better at classifying in computer vision? What is GentleBoost ...
1
vote
1answer
31 views

Can you use a Bayes classifier to determine if something is NOT in a defined class?

I know I can use a Bayes classifier to determine if something is one of N classes, but can I also determine if something is NOT in any of the predefined classes? Or will a Bayes classifier only find ...
0
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0answers
41 views

What level of maths do I need for artificial intelligence? [duplicate]

I want to learn maths for artificial intelligence. I heard that main areas of mathematics for AI are Multivariable Calculus, Linear Algebra, Probability and Statistics and Discrete Mathematics. But ...
1
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3answers
48 views

kNN: how to improve Spam classification?

Currently I'm trying to classify spam emails with kNN classification. Dataset is represented in the bag-of-words notation and it contains approx. 10000 observations with approx. 900 features. Matlab ...
2
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2answers
42 views

What kind of model is used by 20 Questions?

Which kind of machine learning concept / model is used in 20 Questions? Is this kind of thing best solved by a neural network? Where I can read something about it?
3
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2answers
52 views

Physical Meaning Behind Matrix Factorization

As we all know, Matrix Factorization is an effective method to do rating prediction jobs in recommender systems. Thanks to the work of Yahuda Koren. My question is why MF can do this job? What's the ...
2
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0answers
27 views

Difficulty in understanding a graphical model in training

Yue et al [1] and Chong & Wong [2] apply a cognitive map for goal-oriented decision making. The basic premise is that we need to find out the initial states that will give us the desired goal ...
2
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2answers
73 views

Soft Margin Loss and Conditional Probabilities

Consider the following soft margin loss function: $\max(0, 1-yf(x))$. I have the problem of needing to compute the conditional probability $p(y|x)$ corresponding to this function and am having ...
0
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0answers
13 views

Supervised learning based on phase space representation

Phase space learning Paper1 and Paper2 in neural network represents the input in higher dimension in auto associative learning. So, the network functions as an auto-associative memory where dynamical ...
0
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0answers
17 views

web content “mining” using supervised learning tequniques

We're accessing an API of a web system for obtaining product information. We require some additional information, which is not available through the API. This information is publically available for ...
3
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1answer
26 views

Decision Tree with Unbalanced Data

I have a data set with two classes: one class has at most 2000 members while the size of the second class is unlimited, though it is typically in the hundreds of thousands. I have read that it is ...
3
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1answer
162 views

Does there exist a data compression algorithm that uses a large dataset distributed with the encoder/decoder?

If my goal were to compress say 10,000 images and I could include a dictionary or some sort of common database that the compressed data for each image would reference, could I use a large dictionary ...
1
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1answer
33 views

parallelizing $k$-means

I'm having trouble thinking about the following. If we have two machines 1 and 2 that evenly split a set of data points, does $k$-means separately, then averages the result, does this agree with just ...
3
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1answer
40 views

Classification algorithm for high dimensional data which is uniquely definable in a very small sub-space

I am new to machine learning, so forgive me if I am doing something absolutely absurd. I have a classification task (~100 classes) and have about 2 million training data points in a 2000-dimensional ...
-1
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1answer
45 views

In back propagation why is this necessary, o (1 - o) [duplicate]

To calculate the error in back propagation you would use, (target_output - actual_output) * actual_output * (1 - actual_output) So what does, actual_output * (1 - actual_output) solve? Wouldn't, ...
3
votes
1answer
37 views

ML Algorithms to discriminate “known” from “unknown” instances

I'm classifying different electrical devices based on features extracted from their electricity consumption into a household-specific model built from around 10 devices. Now I want to detect whether a ...
1
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1answer
50 views

How are Bayesian Nets, Hidden Markov Chains, Conditional Random Fields and Neural Nets related?

I am having an AI exam in two weeks, and I am still figuring out certain concepts and ideas, related to Bayesian Nets, Hidden Markov Chains, Conditional Random Fields and Neural Nets (yes it is all ...
3
votes
1answer
33 views

Proving $\log (N)$ mistake bound is “tight” for a learner when learning thresholds

I'm studying the online learning model and the Halving algorithm. We've seen the threshold problem: The domain is $X=\left\{ 1,2,...,N-1\right\} $, the label set is $Y=\{-1,1\}$ and the hypotheses ...
3
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0answers
45 views

Is machine learning all about statistical regressions at its core? [closed]

For the past several months I've been interested in some Machine Learning and I can't help but notice that nomatter what kind of learning algorithm I'm using - at its core lies a simple polynomial or ...
11
votes
1answer
39 views

Why are diploid (dominant/recessive) genes not used widely in genetic algorithms?

In most implementations of genetic algorithms, the focus is on crossover and mutation. But somehow, most of them leave out diploid (dominant/recessive) nature of genes. As far as my (limited) ...
9
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4answers
22 views

Machine learning - importance of correlation vs. causation

It is a well-known fact that "Correlation doesn't equal causation", but machine learning seems to be almost entirely based on correlation. I'm working on a system to estimate the performance of ...
1
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1answer
71 views

Determining the optimal threshold value for a one-dimensional decision stump classifier

I'm currently trying to find an efficient algorithm to solve a discrete optimization problem that arises when constructing decision trees. The problem is as follows: Say we are given $N$ ordered data ...
1
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1answer
55 views

VC dimension of complement

Let $C\subseteq 2^X$ be a concept class over $X$ and let $\bar{C}:=\{X\setminus c\mid c\in C\}$ be the complement. Show that $VCdim(C)=VCdim(\bar{C})$. Proof: Let $d:=VC_{dim}(C)$, then there exists ...
2
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1answer
73 views

Is Q-Learning ever better than Brute Force?

I am currently learning about the Q-learning algorithm, so I therefore assume that it has some use or purpose. However I currently cannot see how it is in any way useful. In terms of complexity class, ...
3
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1answer
66 views

What are the key differences between Spiking Neural Network and Deep Learning

Deep Learning, now one of the most popular fields in Artificial Neural Network, has shown great promise in terms of its accuracies on data sets. How does it compare to Spiking Neural Network. Recently ...
3
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1answer
61 views

Are expert systems outdated, what are better alternatives to them, if any?

I need to link facts to actions through rules. If a person bought soup 10 times and he is coming at midday every day, then the system should link the fact that the person bought soup so many times, ...
2
votes
2answers
42 views

What values do $y_i$ in training data for binary classification problems attain?

In case of binary classification problem, what are the $y_i$ 's in the training data set $\{(x_1, y_1), (x_2, y_2), \dots (x_n, y_n)\}$? I guess they are from $\{1,-1\}$. Now I see a method for ...
2
votes
1answer
30 views

Solving the part-of-speech tagging problem with HMM

There is a famous part-of-speech tagging problem in Natural Language Processing. The popular solution is to use Hidden Markov Models. So that, given the sentence $x_1 \dots x_n$ we want to find the ...
1
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0answers
41 views

Applications of algorithms to stock trading analysis

There is a new Quantitative Finance SE site. However, I am interested in asking the "CS crowd": What are some interesting key references or surveys on applying algorithms to stock trading ...
2
votes
1answer
21 views

How do I apply patch sized features to larger images?

I've been trying to teach myself some machine learning, and I wanted to ask what seems a simple question, but I've not been able to find any resources that explain the next step. Let's say I am doing ...
5
votes
2answers
87 views

What is usually the next step after showing the VC dimension?

I am new to statistical learning. I have a structure $X$ where I showed its hypothesis class $H$ has VC dimension $d$. All I know now is that I can bound the number of examples by $m\geq ...
3
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2answers
62 views

How to evaluate recommendation engine without ground truth?

I have developed an algorithm which recommends geographical locations to users based on popular trends and their own interests. The dataset is created by my organization. So the user selects a few ...
7
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2answers
152 views

Smallest DFA that accepts given strings and rejects other given strings

Given two sets $A,B$ of strings over alphabet $\Sigma$, can we compute the smallest deterministic finite-state automaton (DFA) $M$ such that $A \subseteq L(M)$ and $L(M) \subseteq \Sigma^*\setminus ...
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1answer
92 views

What program will derive the underlying algorithm in these question-answer pairs (updated)?

Given this set of question-answer pairs, what program will derive the underlying algorithm and provide the correct answer for any question of the same format. Question-Answer Pairs (training set): ...
3
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1answer
72 views

Machine Learning: What program will derive the underlying algorithm in this series?

This is a machine learning question. Given this series of categorical data, what program will derive the underlying algorithm and predict what comes next in the series? Here is the series: B, BA, ...
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1answer
43 views

SVM math question

I'm studying support vector machines and came across this paper. The following equation doesn't make sense to me, especially the part with the 0 ∀i. Any help understanding the basics of SVMs? yi * ...
0
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0answers
25 views

Support Vector Machines as Neural Nets?

This is more of a conceptual question. I have learned about Neural Nets, and I have some clue as to how Support Vector Machines work. I read somewhere however that given the appropriate kernel (is ...