0
votes
0answers
17 views

time complexity and space complexity for HMM forward recursion

When Reading the HMM models, I found the following discussion on the time complexity and space complexity regarding forward recursion. I am sort of confusing on the reason of getting O(K^2N) and ...
0
votes
0answers
19 views

Strategy for building best fit multiple regression model with time lagged variables

I am building a multiple regression model - wrapped in a function - with one dependent variable and a dozen independent variables. The reason why I am building a function is that I need to do this ...
-1
votes
0answers
33 views

Performance and Parallelization of Dimensionality Reduction Algorithms [closed]

I'm trying to implement a (nonlinear) dimensionality reduction algorithm (and I am new to the field). Now, my question is : How much can I boost the performance of these algorithms (a list of ...
1
vote
1answer
102 views

How can one show a Kmeans solution is unique?

Suppose we are given a distribution P and a constant K. We wish to minimize the kmeans objective w.r.t centers ${C1,..Ck}$: What constraints on $P$ are known to imply that the optimal solution is ...
2
votes
1answer
123 views

Using the appropriate machine learning algorithm

I am not sure if this is the right forum to ask this. I have some data of the houses, like their size(in square meters), if they use aircondition, how many residents live in, I have their electricity ...
0
votes
0answers
44 views

Online Linear Regression with updates on past information

Suppose we have the following algorithm An online linear regression algorithm implemented using gradient descent. The step rate $\alpha$ is calculated using something that correlates to the squared ...
0
votes
1answer
112 views

Pocket algorithm for training perceptrons

When you read about perceptron variants at Wikipedia there is explained an algorithm: Pocket Algorithm It is said that: solves the stability problem of perceptron learning by keeping the best ...
2
votes
1answer
214 views

Kmeans on “symmetric” data

A set is said to be fully-symmetric if for every x in it, negating one of its components results in y such that y is in the set as well. A set is said to be semi-symmetric if for every x in it, ...
2
votes
5answers
177 views

What machine learning algorithm solves this problem?

I want to solve this classification problem. Basically what I have is a sequence of feature vectors $\mathbf{x}_1,\mathbf{x}_2,\dots,\mathbf{x}_N$, and each feature vector is sequential in time. I ...
3
votes
1answer
137 views

How does extreme random forest differ from random forest?

Are they more efficient implementation -- is the difference important from practical point of view, there is R package which implements them. Is it new algorithm which overcomes "generic" ...
2
votes
3answers
259 views

Machine learning algorithm for ranking

I have got a set of elements $X$ which I can describe according to $n$ characteristics. Thus: $$x_i: \{c_{i1}, c_{i2}, \ldots, c_{in}\} \mid x_i \in X $$ where $c_{ij}$ is the (numerical) evaluation ...
-2
votes
1answer
114 views

How could a t-test be used for comparing two ML algorithms?

I am new to ML, and I am reading a paper about ML comparison. It underlines the comparison between two algorithms based on the t-test but it does not describe the process further. I know what a ...
0
votes
2answers
201 views

Learning Algorithms/Neural networks books? [duplicate]

Possible Duplicate: Machine learning cookbook / reference card / cheatsheet? Machine learning self-learning book? What are some good theoretical and practical machine learning algorithms ...
1
vote
0answers
156 views

Ultimate Jedi Challenge - Multiarmed Bandit / Reinforcment Learning / advanced AI with a lightsaber twist [closed]

1. Ultimate Jedi Challange - the core Background story You are a Jedi master who wants to prepare a training program (online-algorithm) for his apprentice - Luke. Luke needs to practice several ...
4
votes
1answer
113 views

What are speed differences beetwen ML implementations in different languages?

I am trying to write my own ML library. For speed reasons I started out writing things in C using BLAS, but then I learned that NumPy and Theano also use BLAS. I am wondering if there are huge speed ...
8
votes
3answers
188 views

What is the most efficient way of training data using least memory?

This is my training data: 200,000 Examples x 10,000 Features. So my training data matrix is - 200,000 x 10,000. I managed to save this in a flat file without having memory issues by saving every ...
0
votes
1answer
165 views

Entering values into a linear regression / gradient descent algorithm

The instructor of the machine learning course I've been taking whipped this algorithm at my head without explaining how to apply it to a training set. ...
4
votes
2answers
247 views

On-line detection of over-fitting in neural networks

As we train a neural network, we have access to the error-rate (both on training, and test patterns). What are standard techniques to use this information to stop the learning as quickly as possible ...
3
votes
1answer
139 views

Minimisation algorithm for a mix of discreet and continuous parameters?

I have a minimisation problem in which the parameters are a mix of integers and scalars. Some of the integers have a small range, around 0-10 but others range in the thousands. To give some context, ...
1
vote
0answers
134 views

Calculating VC-dimension of a neural network

If I have some fixed non-recurrent (DAG) topology (fixed set of nodes and edges, but the learning algorithm can vary the weight on the edges) of sigmoid neurons with $n$ input neurons which can only ...
2
votes
1answer
223 views

Open source implementation elastic net in C or C++

Can anyone provide or point me to a freely available implemention of Elastic Net in C or C++?
11
votes
2answers
438 views

Best bandit algorithm?

The most well-known bandit algorithm is upper confidence bound (UCB) which popularized this class of algorithms. Since then I presume there are now better algorithms. What is the current best ...
0
votes
0answers
96 views

having trouble applying hidden markov models to my game [duplicate]

Possible Duplicate: having trouble applying hidden markov/machine learning models Happy New Year! I’m having a problem applying hidden Markov models to a game I’m building to learn about ...
9
votes
1answer
145 views

Run-time analysis of common machine learning algorithms

Does anyone have reference to a summary of run-time analyses for common machine learning algorithms (different flavors of NN, SVMs, etc)?
4
votes
1answer
724 views

2D object recognition using MATLAB

Have you any idea about implementing 2D object recognition with MATLAB? Which characteristics of objects can feed a neural network? It's my training data-set (provided by ETH University of ...
13
votes
6answers
1k views

Data mining: How should I go about finding the functional form?

I'm curious about repeatable procedures that can be used to discover the functional form of the function y = f(A, B, C) + error_term where my only input is a set of ...
1
vote
0answers
180 views

Confusion in MLE and EM [closed]

I was trying to read through Maximum Likelihood Estimation(MLE) and Expectation and Maximization(EM) algorithm. But while reading them, I got two interpretations. I am trying to post my questions, ...
3
votes
0answers
181 views

Statistical query model algorithms?

Can you give me examples of machine learning algorithms which learn from the statistical properties of the dataset not the individual observations itself i.e. employ the statistical query model?
9
votes
2answers
1k views

How does random forest generate the random forest

I am not an expert of random forest but I clearly understand that the key issue with random forest is the (random) tree generation. Can you explain me how the trees are generated? (i.e. What is the ...