Questions tagged [statistics]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
4
votes
2answers
770 views

What empirical evidence do we have for or against a correlation between fault density and LOC?

LOC = lines of code KLOC = Thousand lines of code Fault (or defect) density = number of reported bugs per line of code. Software artifact = function, class, module Reading research papers on fault ...
0
votes
1answer
30 views

Efficient random sampling from large discrete distribution

I have a random variable $X$ that can take finite values in $\{X_1, ..., X_n\}$ with probabilities $\{p_1,..., p_n\}$. Is there a computationally efficient way to sample a number from this set? My ...
1
vote
0answers
11 views

Distributed Graph Consensus to fit a distribution?

$G$ is a strongly connected graph with nodes $V$ and edges $E$. Each node $v_i$ receives a sample $x_i$ from a Gaussian $\mathcal{N}(\mu,\sigma^2)$ with unknown mean and variance. The objective is for ...
1
vote
0answers
15 views

Distribution independence property testing

I have been reading the proof in the following paper, and I am unable to understand some parts in the proof. This paper shows that a distribution $A$ over $[n]\times[m]$, $n\geq m$, can be $\epsilon$-...
1
vote
2answers
48 views

Sliding window max/min algorithm without dynamic allocations

I'm working on a suite of DSP tools in Rust, and one of the features of the library is a collection of windowed statistics (mean, RMS, min, max, median, etc) on streams of floating-point samples. For ...
0
votes
0answers
22 views

Simple Bayesian Question

I have the following Bayesian Network. I have worked out the following: P(H) = P(H|D) + P(H|¬D) = 0.5 + 0.1 = 0.6 P(D|H) = (D)∗(P(H|D) +P(H|¬D)) = 0.3∗(0.5 + 0.1) = 0.18 How do I compute the ...
1
vote
0answers
28 views

EM algorithm - What happens with the standard deviation?

What have you tried? So I watched this video. According to the video, we've to calculate the variance $\sigma^2$ as follows: $$ \sigma_{k}^{2} = \frac { p_{1} \left(x_{1} -...
0
votes
1answer
38 views

PCA applicability

I understand that PCA takes a data set with input size, with output labels, and reduces the inputs to a set of principal components size r, where r < n. My question is whether or not this can be ...
0
votes
0answers
43 views

Most popular path in weighted cylic directed graph

Context I have a graph $G=(V,E)$ with weighted edges, all weights are positive integers $w(e)\in\mathbb{N}\setminus\{0\}$. The weights represent the popularity/count of each edge, for example $w(e) = ...
1
vote
1answer
122 views

Approximate max weight path in directed graph

Context This question is related to the fact one can't use Bellman-Ford to find max weight paths in directed graphs with cycles. The reason is that giving a new graph $\tilde{G}$ with negative weights ...
0
votes
1answer
88 views

Chebyshev’s inequality problem in one exercises I can't understand if I did it right or not

This is what do I have to solve: Byron Book: Exercise 8.3 chapter 8 Verify the use of Chebyshev’s inequality in (8.6) of Example 8.16. Show that if the population mean is indeed 48.2333 and the ...
2
votes
0answers
20 views

Separating labelled points with a plane, minimizing label variance

Suppose we have observations with associated labels $\{({\bf x}_1, y_1), ({\bf x}_2, y_2), \dots, ({\bf x}_n, y_n)\}$ where ${\bf x}_i \in \mathbb{R}^d$ and $y_i \in \mathbb{R}$. Can we efficiently ...
1
vote
0answers
13 views

Tracking approximate values of specific percentiles

At the moment I use HdrHistogram to track approximate distribution of a stream of values. But I don't really need all percentiles, just three of them. Is there some algorithm to track specific ...
1
vote
0answers
21 views

Differential Privacy with only positive noise

The Laplace mechanism is a standard way of making the output of a function $f$ differentially private. More concretely, let $\Delta_f$ be the sensitivity of $f$, i.e. the maximum value by which the ...
0
votes
1answer
38 views

How to implement conditional probability distribution on set-valued Random Variables

I'm trying to implement conditional probability distribution when the events of two RVs are sets. If I try to extrapolate concepts from real or categorical variables to sets things become confusing ...
2
votes
1answer
38 views

Averaging a list of variances

In a setting where I have n clients each owns a subset of the dataset, each computes the mean and variance on his data and send them to the server. The server would average all means and variances. ...
2
votes
1answer
53 views

Is this statistical group summation unambiguously reversible?

Let $X$ be a finite multisubset of $\mathbb{N}^2$. Let's introduce the following notation: $A$ is a set of all first elements of pairs from $X$ and $B$ is a set of all second elements of pairs from $X$...
0
votes
0answers
16 views

what is instrument validation in computer science?

I'm writing an assignment involving some statistics comparing different implementation methods for web applications. I'll be using some downloaded software and web pages I create, on both virtualized ...
2
votes
0answers
23 views

Algorithm to mapping given probabilities to empirical probabilities

Consider following problem statement: You have given $n$ actions. You can perform any of them. Each action gives you success with some probability. The challenge is to perform given finite number of ...
0
votes
1answer
80 views

Find the average number of steps to sort an array by randomly selecting two elements

I have sequence of an unique numbers from 1 to 10 in randomly order (for example: list = [7, 5, 3, 4, 2, 6, 10, 1, 9, 8]). I can choose two random number and if the list from left number larger then ...
1
vote
1answer
19 views

SGD statistical guarantee

I have a question regard online learning with SGD. Is there a way to give a statistical guarantee that the value obtained after $n$ samples deviates at most $\epsilon$ from the real value? Thank you ...
0
votes
0answers
27 views

How to handle distribution of values with same attributes into different classes

I'm a student studying a data mining course and have come across a problem. I need to explain the problem with the help of an example scenario as I do not know how to explain the problem in any other ...
1
vote
1answer
46 views

Chebyshev inequality comparison

Given $n$ distinct values $(x_i)_{i=1}^{n}$ with mean $\mu$ and standard deviation $s$, for all $i$, we have $|x_i−\mu| ≤ s \sqrt{n − 1}$. How does this inequality compare with Chebyshev inequality as ...
1
vote
1answer
327 views

Efficiently selecting a random subset of size $m$ from a set of size $n$

This is a cross post of my question here on math.se. I have a list of $n$ items and would like to randomly select an $m$ set from it efficiently (in terms of time complexity). Also, I want all ...
2
votes
0answers
44 views

In a machine learning system, why use differentially private SGD if our input data is already perturbed by a DP mechanism?

I'm trying to implement my own version of a deep neural network with differential privacy to preserve the privacy of the parties involved in the training dataset. I'm using the method by Abadi et al. ...
0
votes
1answer
39 views

Gaussian distribution with condition?

What does this expression mean? Normal distribution with condition I am reading a research paper and found the following expression (Eq.28 in the paper below). It means a Gaussian distribution, but ...
1
vote
2answers
63 views

Algorithm for Estimating Number of Unique Monthly Visitors

Is there a way to estimate the number of unique monthly visitors to a site based on a limited sample of one week of data? I have information about when a given user visited the site. This isn't as ...
5
votes
1answer
689 views

What is the optimal algorithm for playing the hangman word game?

Suppose we are playing the game hangman. My opponent and I both have access to the dictionary during the game. My opponent picks a word from the dictionary with knowledge of the algorithm which I will ...
1
vote
1answer
38 views

Minimizing Trimmed Distances

I'm trying to understand what is the minimum of the following function, $$ f(\mu) = \frac{1}{n}\sum_{i=1}^n F\left(\frac{\pi(i)}{n}\right) (x_i - \mu )^2 $$ where $F$ is a step function that assign $...
0
votes
0answers
32 views

Does this problem have a formal name?

I have come across the following problem but am unable to understand the solution for it. Hence I would like to know if it has a formal name then, I can search for it and read about it in more detail. ...
0
votes
0answers
45 views

How to find clusters of a set of points in n-dimensional space that are furthest from unwanted points

I have a list of 25 points and their coordinates in a 512-dimensional space. I have 8 target points and 17 points I need to avoid (the 17 points to avoid also have differences in priority of how ...
1
vote
1answer
152 views

Amount of expected loop iterations when searching an array by random index

Lets say we have an array A of size n. It has 1 as its first index and n as its last index. It contains a value x, with x occurring k times in A where 1<=k<=n If we have a search algorithm like ...
0
votes
0answers
16 views

Kullback-Liebler Divergence

For $P(x)=N(\mu,\sigma^2)$ and $Q(x)=N(0,1)$ I am supposed to calculate $KL(P(x)||Q(x))$, here is what I did \begin{align*} KL(P(x)||Q(x)) & = \int P(x) \cdot \log\left(\frac{P(x)}{Q(x)}\...
3
votes
1answer
161 views

Measures of performance in machine learning

I'm new to machine learning and struggle to interpret the results I get from different measures of performance. If for several prediction models I have e.g. accuracy, precision, recall, F1, FPR, and ...
1
vote
0answers
77 views

Suggestion for a good statistics book for computer scientists, in preparation of machine learning

We (a group of CS postdocs and Ph.D. students) are starting a shared reading of a machine learning book ("An Introduction to Statistical Learning", James, Witten, Hastie, Tibshirani). Before diving ...
2
votes
0answers
38 views

The No-Free-Lunch Theorem and K-NN consistency

In computational learning, The NFL theorem states that there is no universal learner. For every learning algorithm , there is a distribution that causes the learner to output a hypotesis with a large ...
2
votes
0answers
28 views

What is the purpose of standardization in machine learning?

I'm just getting started with learning about K-nearest neighbor and am having a hard time understanding why standardization is required. Reading through, I came across a section saying When ...
3
votes
1answer
54 views

Estimation of the number of solutions by Counting

This is a question from a quantum computation textbook. Consider a classical algorithm for counting the number of solutions to a problem. The algorithm samples uniformly and independently $k$ times ...
0
votes
0answers
53 views

What kind of standard deviation must be used in optimization algorithms?

I would like to ask about the standard deviation of objective function value. There are two types of standard deviations: Population standard deviation Sample standard deviation In metaheuristic ...
0
votes
1answer
25 views

Assumption of a generation of the dataset by a probability distribution

Consider the following paragraph from the deeplearningbook The training and test data are generated by a probability distribution over datasets called the data-generating process. We typically ...
0
votes
1answer
76 views

How can we get small test error reducing only train error?

My question is about mathematical part of machine learning algorithms, especially about using it in neural networks. We train network reducing train error and I was thinking about how then test error ...
3
votes
3answers
108 views

How good (or bad) is my makeshift PRNG?

Say I have designed a makeshift PRNG for my personal amusement, now I would like to see how good it is. How do I benchmark its "randomness"? Ideally, I want to know a statistics test, such that if I ...
1
vote
0answers
33 views

How to go about designing a quiz that changes difficulty based on user performance?

I thought about using a machine learning algorithm to learn the performance patterns of the quiz taker and model the next quiz based on how he/she performed. So each question will have a difficulty ...
2
votes
2answers
57 views

identify abrupt frame changes in a video

The frames of live streams or videos, in general, do not flow smoothly. A sports game would have multiple cameras recording the game and hence, there will be camera switches in the stream. I am ...
1
vote
2answers
274 views

probability of collision

my data's range is from 1 to 9 and I have two subsets of integers from this range. the hash function takes each of this subsets and calculate product of these three integers and maps this set to the ...
0
votes
0answers
43 views

Optimize Algorithm For Shut in Box Game

This game is a simplified version of Shut the Box. There are 9 tiles (1,2,3,4,5...9). The initial tiles are unflipped. You have 2 dices. Each round, the player rolls the 2 dices and their sum is S. ...
1
vote
1answer
553 views

Is there a fast algorithm for computing the rolling mode of an array of integers?

I was wondering if there exists an efficient algorithm for calculating the "rolling mode of an array of integers. By rolling mode I mean that we have an array of integers of size $n$ and a sliding ...
2
votes
1answer
2k views

Median of two sorted arrays of different size in logarithmic time?

The solution given in Cormen is as follows: Reading this solution, the first doubt that comes in my mind is what if the median lies in array B. According to this solution, we are applying binary ...
0
votes
0answers
30 views

Locality sensitive hashing with non-scalal values

Locality sensitive hashing works well when matching is between vectors of scalars, but I now need to extend LSH to compare matrices. Each matrix is formed of n readings from m sensors forming a n by m ...
0
votes
1answer
63 views

How to find a possibility of match in Naive Bayes Classifier?

My math level is very very poor so I can't get the statistics. Can anyone explain in simple words? I.e. if I have frequency data: ...