1
vote
1answer
54 views

How is PI used to predict weather patterns?

I've heard that using PI to predict weather patterns is possible. I would like verification on this, and how this is possible. I can't seem to find any other sources explaining this concept. My ...
0
votes
1answer
45 views

How can I figure out the total solutions in this Combinatorics problem?

Imagine you have a sequence of cards, each having a unique set of features. Example features : letter (A, B, C), number (1, 2, 3), and color (Red, Green, Blue) Some example cards : A1Red, B1Blue, ...
0
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1answer
35 views

How to complete a table of probabilities ?

Im baffling myself as to why I cannot understand where it came from. Someone please explain to me like I'm five. $$\begin{array}{c|c} x & p(x) \\ \hline 0 & 0.73 \\ 1 & ? \\ 2 & 0.06 ...
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0answers
41 views

Creating feature vectors with a high degree of entropy from the actual training data for neural network?

Note: My upper level math skills are not in good shape and end around 1st semester calculus. I am looking for guidance that would help me find a known algorithm that does what I need in the open ...
2
votes
1answer
434 views

Bottom to top explanation of the Mahanalobis distance?

I'm studying Pattern recognition and statistics and almost every book I open on the subject I bump into the concept of Mahanalobis distance. The books give sort of intuitive explanations, but still ...
0
votes
1answer
125 views

Expression for Sum of Multivariate Gaussian Random Vectors

Consider two multidimensional random vectors $x$ and $z$ having Gaussian distributions $P(x)=N(x\mid\mu_x,\Sigma_x)$ and $P(z)=N(z\mid\mu_z,\Sigma_z)$, respectively, together with their sum $y=x+z$. ...
1
vote
1answer
411 views

Softmax function and modelling probability distributions

Hinton in his neural network course on Coursera says that "Any probability distribution P over discrete states (P(x) > 0 for all x) can be represented as the output of a softmax unit for some inputs." ...
1
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0answers
113 views

Is kernel density estimation a GMM with uniform mixture weight?

recall that for a Gaussian Mixture Model, the density of p(x) (multivariate) is $$P(x) = \Sigma_{i=1}^{C}\pi(c_i)\mathcal{N}(\mu_i,\Sigma_i)$$ On the other hand, non-parametric density estimation ...
1
vote
1answer
251 views

Stuck with handling of conditional probability in Bishop's “Pattern Recognition and Machine Learning” (1.66)

I've just started working through the book, and I'm stuck with how the author handles conditional probability in (1.66). The context is as follows. In this chapter we are working with a curve ...
0
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2answers
257 views

Probability of market movement / Trends

If you imagine a scale from -100 to 100, if the market has moved up from 0 to 40, what is the probability is will continue to 100? There is a 50-50 chance to move up or down from 0, but what is the ...