Tagged Questions

0
votes
1answer
47 views

Comparing two points corresponding to two different normal distributions

I have two multi variate normal distributions N1 and N2. Say two points p1 is from N1 and p2 is from N2. I want to get some statistical features from these two points. How can I do it? I need a ...
0
votes
2answers
75 views

Estimating probabilities using Bayes rule?

I am working on a past exam paper. I am given a data set as follows: Hair {brown, red} = {B,R}, Height {tall, short} = {T,S} and Country {UK, Italy} = {U,I} (B,T,U) (B,T,U) (B,T,I) (R,T,U) (R,T,U) ...
0
votes
0answers
37 views

How to calculate entropy in log Scale?

I'm working on a problem , where a function returns the Log probability of P(X=x) . Now I would like to find the Entropy of X. But since the probabilities I get are log probabilities, again taking its ...
0
votes
0answers
41 views

May I get HMM calculations Checked?

I was trying to understand Hidden Markov Model(HMM). I was working out some examples. The first work out was on initial probability, transition probability and emission probability. I was trying to ...
0
votes
0answers
49 views

Are my HMM calculations going fine? [closed]

I was trying to understand the hidden Markov model (HMM) and to do some calculations, and I got some doubts. I attach my study in this Google Drive File. Can you check if my calculations are fine? I ...
2
votes
0answers
100 views

Kullback-Leibler vs Hellinger Distance

I am working on this problem in which I have a dataset of n-dimensional examples that come from different and unknown distributions. Given a new sample, I wish to find k examples from the dataset that ...
0
votes
0answers
69 views

What is forward and backward probability? [closed]

I am trying to understand Forward-Backward probability. I understood Transition Probability, Emission Probability, Viterbi. But getting confused with Forward-Backward. I was trying to work out the ...
2
votes
0answers
65 views

Random sampling for estimating mutual information - Time complexity and sampling error?

I have a dataset and I want to compute the mutual information (MI) for a selected set of variables. The dataset is large enough so that computation of the MI may take undesirably long time. Can I just ...
0
votes
1answer
154 views

Combining results of two classifiers to better classify a data-point

Suppose that a classifier A classifies a data-point $x$ in class LA1 with probability PA1 and class LA2 with probability PA2 (with LA1 != LA2 and PA1>PA2); and that a classifier B classifies a ...
1
vote
4answers
263 views

Methods & CRAN packages to predict probability using neural networks or others machine learning algorithms

I have a medical database containing 7 input variables (4 are binary) and a binary outcome variable (Survival: yes/no). My objective is to train and test an algorithm that predict probability of ...
2
votes
0answers
14 views

Maximizing choice

There are N number of people and X amount of objects with different values. Each person will choose an object and will obtain that objects value. If multiple people choose the same object then the ...
4
votes
1answer
129 views

Confusion related to semisupervised learning in random walk

I am trying to understand the semi supervised learning in random walk. Lets say I have 10 classes and I have some labelled and unlabelled points. Now, I need to find the labels for the unlabelled ...
0
votes
0answers
65 views

Binary classifier probability measure?

I've the following situation. I've a binary classifier which classifies input feature vectors into either of two classes 'y' or 'n', along with the probability of it being in either of the classes ...
1
vote
1answer
172 views

How to convert multiple ranking scores into a probability distribution?

I would like to create a topic distribution for a document. The current model I am trying to implement is: for each sentence in the document, I am getting a topic assignment with a score, e.g. "1st ...
5
votes
1answer
245 views

Getting probabilities over 1 in positive and unlabeled learning

I have a question regarding PU-Learning, which deals with learning from positive-labeled (no labeled negative examples) and positive/negative-unlabeled data. Particularly, my question is about the ...
1
vote
1answer
65 views

Probability of observed data in HMM

In a given Gaussian mixture model with observed continues variables $Y$ and latent discrete variables $X$ I want to apply the forward-backward algorithm in order to compute the marginal posteriors ...
14
votes
2answers
330 views

Combining classifiers by flipping a coin

I am studying a machine learning course and the lecture slides contain information what I find contradicting with the recommended book. The problem is the following: there are three classifiers: ...
6
votes
1answer
68 views

Beyond Fisher kernels

For a while, it seemed like Fisher Kernels might become popular, as they seemed to be a way to construct kernels from probabilistic models. However, I've rarely seen them used in practice, and I have ...
0
votes
1answer
163 views

pLSA - Probabilistic Latent Semantic Analysis, how to choose topic number?

I am approaching to pLSA (Probabilistic Latent Semantic Analysis) in this period, to apply it to biomolecular annotation prediction. A very simple question: how to choose the number of topics/classes ...
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 ...
4
votes
1answer
179 views

Learning to create samples from an unknown distribution

I am interested in new generating samples to approximate some unknown distribution X, where each new sample is a real-valued vector. The purpose it to be able to create a new (arbitrary large) ...
0
votes
1answer
146 views

How to compute mean vector and covariance matrix of equal distributions?

This question is an extended version of this one. As you can see here, two distributions are equal, I need to compute the parameters a,b,c,d and e. Could you show me a way to do that? Assume a ...
2
votes
1answer
141 views

How to get started in data-relation algorithms and mathematics?

I am very interested in the concepts and discussions taking place here. However, I'm not entirely sure what this field of study is called or what the many branches of study are being discussed here ...
1
vote
2answers
233 views

Metric for probability based classification

I am doing a system for classifiying documents. The project demands the use of probability based output. So a sample will have a probability for belonging to each class. For now I use logistic ...
4
votes
1answer
187 views

What is the $i$th sufficient statistic in the EM algorithm for Gaussian mixture models?

I am reading up on the EM algorithm for Gaussian Mixture Models, and there is consistent reference to the $i$th sufficient statistic. What is this, and why is it relevant to the algorithm?
9
votes
1answer
804 views

What is the best way to learn the fundamentals of probability required for machine learning algorithms?

I took a probability course in university a few years ago, but I'm going through some machine learning algorithms now and some of the math is just befuddling. Specifically right now, I'm learning ...
5
votes
2answers
316 views

Deriving mathematical model of pLSA

After knowing how LSA works, I went on continue reading on pLSA but couldn't really make sense of the mathematical formula. This is what I get from wikipedia (other academic papers/tutorial show ...
3
votes
1answer
120 views

White box machine learning probability estimator

Have you ever heard about Child-Pugh cirrhosis score? There are five features, each feature is discretized in three intervals. For each interval you get a point, eg 1 for the first, 2 for the second ...