All Questions

I want to evaluate several forecasting methods on the taylor time series using cross-validation. How do I go about selecting the hyper-parameters for the methods? ...

In a machine learning context, does it make sense to have both a measurement and its absolute value transformation as features? There are already ~120 features in this predictive model (an elastic ...

I am reading the following article: https://arxiv.org/pdf/1803.00385.pdf On page 3 they explain how the losses for two discriminators (D1 and D2) is determined. D1 separates true upright image from ...

I am looking for a data set containing images of pedestrians/cyclists with static background and given camera calibration information (intrinsic and extrinsic) for a scene. I have already found EPFL ...

If repeated measures anova is analogous to random-intercepts regression and regular anova is analogous to multiple linear regression because of the F-statistic. Is GEE logit or GEE poisson or ...

I am trying to create code in Matlab that runs a Brown-Forsythe test on an unbalanced two-way ANOVA. I am having difficulty figuring out the actual math behind this test and how to do it. I have read ...

I have a question regarding a translation in odds ratio curve OR(x). More specifically, let's say we have an OR(x) which we get using logistic regression. We look at the interval bounded with 25% and ...

Problem with non standard question about latent variable applied non-linear discrete choice models. I'm having issues because I couldn't find in the material I have in my possession any example ...

I'm curious about the procedure on how to execute a hypothesis test for following hypotheses on a 10% significance level: How do I calculate the test variable? For which levels of Z do I reject ...

I would like to use two algorithms then evaluate their result both of them are based on logistic regresion based on gradient discent the second model contains aditional features I would like to ...

I want to back-calculate the minimum sample size for an experiment. I have a known mean and standard variance of a statistical population. From the statistical population I chose two samples with ...

Projectile motion is given by a function $y = -9.81 x^2 + ax + b$ for some parameters $a$ and $b$. I'll simply assume for $x$ values to be distanced by 1, so $x_t = t$. I can then easily generate ...

I am comparing a selection of values which come from a non-normal distribution to 0. I've done a wilcoxon in python: result = scipy.stats.wilcoxon(values) my W ...

Is the value supplied to the shrinkage regularizers (l1 and l2) in Keras the inverse of the lambda coefficient? e.g. ...

I'm a beginner in machine learning. I was reading http://ciml.info/ 5.9 Bias/Variance Trade-off According to this book: The trade-off between estimation error and approximation error is often called ...

I am having hard time understanding the use of nested and non-nested models. According to Ben-Akiva's description the nested models are blue bus/red bus problems, where the choice set has multi ...

I have a system of generally known behavior, and some non-uniform measurements of that behavior (let's say without measurement error). Now I want to fit a simple function to a subset of the ...

I am building a Bayesian model where I to put shrinkage priors such as spike and slab, horseshoe prior, etc on some parameters for feature selection, but I am not able to decide which one is the best. ...

I ran the Mann-Whitney in SPSS. In addition to the U, the output generated the Wilcoxon W and the Z score. Why would the W and Z be present in the output? I cannot explain them being present. Also, ...

I am running a model with which I want to explain students' performances. I lagged my main independent variable by two years. Now, my results show a negative coefficient for the two years lagged ...

I am working on a deep learning research and came across the following problem: I have a network (let's call it A) that performs a certain task with X% ...

Suppose one estimates a linear model $$ y=\beta_0+\beta_1 x+\varepsilon $$ and finds that $\hat\beta_1>0$ and the $p$-value associated with $\hat\beta_1$ is lower than the chosen significance ...

I wrote this very simple python code: X = np.array([[1,0], [0, 1]]) Y = np.array([0, 0]) clf = sklearn.linear_model.Lasso() clf.fit(X, Y) then I got the ...

I run a log linear model $$\log(Y)=\alpha + \beta X + \epsilon$$ and wonder how to calculate the mean of predicted values, in the same dimension as the initial (untransformed) variable Y. I would ...

I don't know when to use Type 1 or Type 2 error when given a question. For example, if given data and told to test if there is a significant regression of Y on X and also calculate the correlation ...

I have the following data: ...

Suppose that the true model is given by Y=0.3+X1+X2+X3. Assume we have 100 training examples where each covariate vector (X1, X2, X3) is randomly drawn from some distribution P and Y is generated ...

I have a data set of about 10,000 rows, 6 columns "First Name", "Last Name", "Gender", "Age", "Marital Status", "Occupation" I want to reduce the data set to 350 by these selection criteria; ...

Is there any measure in the literature that allows measurement of similarity between two variables by considering their magnitude? For example, variable ‘a’ and ‘b’ both take values in range [0,1]. ...

Having troubles with the lag specification of a VAR-model. The purpose of the model is to measure orthogonal impulse/response function of oil price shocks on macroeconomic variables, such as GDP-...

So I have a new project where I have to classify different types of damages on microchips. I am new to machine learning and python in general so I am a little bit lost. I have over 100.000 images I ...

Can we still use LASSO even when we have a small number of variables?

I hope my title is phrased correctly, otherwise feel free to rephrase it. This is my first time working with such a data set and i'm trying to understand if a method i'm using is correct. Here is a ...

I have 2 input variables, $X_1$ and $X_2$ that affect output variable $Y$. I can run experiments where I modify the inputs and measure what happens to the output. Now, if $X_1$ and $X_2$ were binary, ...

I'm rather new to Machine Learning but I have been looking into it for a bit now. Specially I've been interested in text classifying solutions and seen how a high level of success has been achieved in ...

As part of some preliminary research, I'm experimenting with a random forest classification model for predicting whether the S&P 500 will be higher or lower at tomorrow's close versus today's ...

I want to estimate a relationship of the form: $$y=ax^b\times\epsilon$$ If I log this model i get: $$\log(y)=\log(a)+b\log(x)+ \log(\epsilon)$$ If I then proceed and estimate this model using a ...

can anybody clarify that how dempster Schafer theory works how to calculate the mass and bel in this theory? suggest me any solved example to get some knowledge related to this. R&D on this theory ...

I have an equation with 2 variables, x and y. x and y are random variables. The question is: Ln(Z)=aLn(x)+bLn(y)+c a,b and c are constant and already determined. I need to calculate CDF of Ln(Z). I ...

According to this Wikipedia entry, "Mu was derived from the Egyptian hieroglyphic symbol for water, which had been simplified by the Phoenicians and named after their word for water". So, my question ...

I have been going through Gaussian Processes. In one of the code I stumbled upon there is this statement, I am not quite sure of the parameters that are passed to initialise it. Please help me. ...

I am using BATS on a univariate time series model. I have observed strange behaviour. I have data from 2016 to till date (weekly level). If actual are considered from 2016 to 2019 May, I have used ...

In social science field (particularly Finance and Operations Management), we usually need to prove or disprove hypotheses of the type: X are positively associated with Y. One of the typical method to ...

I am planning a research which will go as follows, There will be ten participants and each will perform the same exercise. However they will be wearing the variant A or variant B of the garment we ...

I am doing competing risk regression. I have three possible functions and one of them produces completely different results than other two. In my dataset I have time to event, status (censored=0, ...

I have got a balanced dataset of 10 different classes $y\in\{0,\dots 9\}$. After fitting a ML model I get classification results $y^*$. Despite the data being balanced, the results are not. I want a ...

I've developed a simple Monte-Carlo simulation. Output of this simulation is a histogram. This histogram is possibly a log-normal distribution, but I don't want to assume that. But I do know that the ...

I am trying to run a SOM for my both qualitative data in five-levels (1-5) and quantitative data for 23 variables. unfortunately, I got this error SOM set.seed(222) g <- somgrid(xdim = 4, ...

I have 20 participants who have watched 18 clips. Every clip belongs to one category of pleasure (p_cat: negative, neutral, positive) and one category of intensity (i_cat: low, medium, high). I have 2 ...

Regarding RNN training, We feed network a network -> point by point from the same time series (or image or smth else). When we “switch from one time series to another”, what should be done or how ...