All Questions

I have tried to read several Hinton's papers about DBN, but still did not understand why in DBN the visible layer and hidden layer are uni-directional. They should transfer the weights to other layers,...

Context I'm tracking auction house prices for items in Guild Wars 2 in a database. They provide an API that allows me to get the item's current buy/sell offer quantities and prices at that moment. As ...

I'm trying to find out what is the learning model of ID3 and Neural Networks -is it global or local for each of them. For decision trees in general I found that they use global learning but for ID3 ...

You have multiple options You need a frequency table with the percentage of only some options However all the variable name without any calculation should be displayed there

Good evening! Last minute panic here, any help will be greatly appreciated! I need to output some preliminary data like the with SAS. All my variables are categorical (1; 0), either depression or the ...

This is just a conceptual question... It seems to me that what is called categorical cross-entropy should be called sparse because with the one hot encoding it creates a sparse matrix/tensor (whereas ...

I'd like help with tackling this toy-problem inspired by an experimental design in the neuroscience literature, as an exercise in learning how to do this sort of thing, and as a way to investigate the ...

I am looking to use ridge regression to predict end of quarter sales revenue. My features are sales pipeline and revenue booked quarter to date. As the quarter progresses sales pipeline will ...

I am working with a problem in an 102C8 sample space, and a binary outcome variable. Accordingly, I have 102 binary indicator variables of which 8 are 1 and 94 are 0 in each record. I am interested ...

I’m analyzing count data (e.g., number of students with suspensions), and the outcomes also have many 0s. The data are also nested (schools within districts). I’m familiar with using Poisson and ...

In the book pattern recognition and machine learning (formula 1.27), it gives $$p_y(y)=p_x(x) \left | \frac{d x}{d y} \right |=p_x(g(y)) | g'(y) |$$ where $x=g(y)$, $p_x(x)$ is the pdf that ...

I have the following toy example to play with the TextCategorizer CNN model in sPacy. Given the distribution of my input dataset, I am expecting the test results to ...

I check the Gumbel distribution article on Wikipedia, it says it is useful to represent the distribution of maxima. But it is not easy to understand how it works? A detailed explanation or examples ...

I'm looking at "An introduction to the bootstrap" by Efron and Tibshirani. I'm struggling to understand the procedure they propose: I don't understand why they subtract the overall mean $\...

In PCA analysis, how can we determine the right factor for a variable? To be clear, I explain with an abstract example. Assume there are 4 variables and the PCA analysis shows that there are 3 factors ...

Consider learning a classifier in a situation with 1000 features total. 50 of them are truly informative about class. Another 50 features are direct copies of the first 50 features. The final 900 ...

I struggling on understanding my professor's solution by having my intuition working incorrectly (maybe). Question (b) states that the flight will depart with empty seats therefore no people will be ...

Suppose $\epsilon$ is a zero-mean univariate random variable noise with finite variance. I would like to find the condition on the function $f$ so that: $$ \exists x \in R \ \mbox{s.t:} \mathbb{E}[f(...

On Wikipedia, I just read that linear regression can be referred to as a discriminative model in the Discriminative Model article. However, I also read in the same article that a discriminative model ...

I've been looking into using mixed effect models for a project, and along the way wanted to experiment with how they'd work on synthetic data. However, I'm confused by the results — if I generate what ...

I have a dataset that looks like this: ...

Say I'm doing a raffle, there's 5 prizes and 50 entrants. Everyone gets one entry. Once a person has won a prize they cannot win another one. I'm wondering what the probability differences are between ...

Let x ~ CN (0,a) and y ~ CN(0,b), with a, b positive constants. Let z = x + y. I need to find the distribution of the vector t=[x; z]. My basic understanding is that vector t is also complex Gaussian ...

I got a problem with arranging the months in order i tried this ggplot(data.frame(bank), aes(x=month)) + geom_bar() + scale_x_discrete(limits = month.abb) But its ...

I am interested in calculating the likelihood of a gaussian process, assuming that we have a continuous record of measurements in an interval, e.g. [0, 1]. In this paper, equation 14 gives an ...

For a set of 48 randomly generated points using runif(), I use the command quantile(x,0.25) to calculate the first quartile in R....

I have a dataset which contains the distribution of session lengths. For each time value it has the number of sessions that lasted for that many minutes. The data follows a logarithmic distribution. E....

Let $x = (x_{t_0}, x_{t_1}, \ldots, x_{t_s})$, where $x_{t_j}$ is a $d$-dimensional ordinal vector taking values in $\{0,\ldots, K\}^d$ measured at time point $t_j$. There is correlation between the ...

I am working with fNIRS data, specifically the NIRS toolbox (made for MATLAB). Through some preprocessing an analysis using a GLM, I get nice-looking data and it plots well, but I do not yet ...

Recently I learnt about DeepSort algorithm which use deep cosine metrics to re-identify objects. However, to my understadning, ...

I was looking at predicting the winner of ncaab games. For this project I have got data on team stats this year and game by game stats. I figure I will need to create a moving average too. I was ...

I will greatly appreciate your advice. I will like to control for family income in my analysis of trends in self-rated health between year 2000 and 2018. The NHIS data from IPUMS that I'm using has ...

We have many continuous features and one categorical feature describing a person. The continuous features are used to train a classifier to predict the binary target variable, the occurrence of an ...

I have a response dataset for twenty-five questions, which measures three grammar topics. The participants are two different English proficiency groups of intermediate and advanced. So, I want to ...

Today I have been asked question the difference between parametric data and non-parametric data. I know about parametric and non-parametric statistics, parametric and non-parametric test, but I have ...

I have inventory forecasts and inventory actuals for every month for the previous year. Results are around 2% forecast error and I want to know the parameters that cause it (I have many parameters ...

I am trying to train a U-Net on my data of shape (3,32,32,32) but my loss function has weird spikes in it that keep on decreasing. I do not understand what inference should I make from this. The code ...

We know the mean and standard deviation of two correlated normal variables X and Y, as well as the confidence interval of the mean and the standard deviation, i.e. $$m-\tau_x \frac{s}{\sqrt{n}}<\mu&...

I have some data included Type of disease Age Gender Bacteria types ... Which test I can do to see effect and it’s interaction Best regards

Considering this entry the distribution of the sum of non i.i.d. gaussian variates is also gaussian. $$ \begin{align*} V = aX + bY &\sim N(a\mu_X + b\mu_Y,\; a^2\sigma_X^2 + b^2\sigma_Y^2 + 2ab\...

So I have a somewhat typical AR(1) process with the phi value being -1, i.e. $$ X_{t} = (-1) * X_{t-1} + Z_{t} $$ How do I go about showing that this covariance stationary process has a unique ...

Formal question: Let $Y,X,X'$ be r.v.s . Let $E_{X}[Var(Y|X)]$ denote the expected conditional variance (i.e. Bayes risk when predicting $Y$ using $X$ under squared error) and $f$ be a bijective ...

I am trying to do a chi squared test in R but I ma not sure it is being done correctly. I am using the Titanic dataset from Tidyverse and seeing if there was an effect of age on survival rate. ...

Is there any example of canonical exponential family distribution with a natural parameter space, that is not open? An $k$ dimensional canonical exponential family means having a p.d.f (w.r.t base ...

What is the function that converts uniform to exponential with the following assumption? Suppose the random variable $X$ follows the arbitrary cumulative distribution $F_{x}(x)$. If the random ...

A random variable $Y$ has the Gaussian distribution on $\mathbb{R}$ with mean $\mu$ and variance $\sigma^{2}$. Select all the necessarily true statements from the following. a. $\mathbf{P}(Y \geq y) \...

I want to use a mixed model to test random effects for between subject factors. Similar questions have been covered before, with answers that it can be done using lme4. (See here and here for some ...

I would like to compare the risk of 2 estimators. Let $X_1,..,X_n$ are $\mathcal{N}(\theta,1)$. I have to show that the average $\frac{1}{n}\sum X_i$ is not admissible if we have prior knowledge that $...

I am sort of green in statistics and I am confused about how to find the error in this situation. Rather than finding the RMSE of the model's estimate, I am trying to determine the real error when the ...

I have data generated by a RCT with a control and treatment group, each with n=300, so N=600. The observations are assumed to be i.i.d.. From that population, I'd like to draw 5 random observations ...