# All Questions

2 views

### How to exact prediction from over sampled data(Undoing oversampling)?

We are oversampling the data to use in logistic regression. Aim is to predict CTR(click probability) which is rare event scenario. I have predicted the probabilities of click but CTR results are ...
2 views

### Deriving the relation $\sum (y_i - \bar{y})^2 - \sum (y_i - \hat{y}_i)^2 = \sum (\bar{y} - \hat{y}_i)^2$

$y_i$ denotes the observed values of $y$, $\hat{y}_i$ are the projected values from the explanatory variables, and $\hat{y}$ is the average. This relation is supposed to hold up when one of the ...
4 views

### Support vector regression (LIBSVM) returns out of range outputs when I use out-of-sample data to predict one step ahead (MATLAB)?

I'm using SVR model in MATLAB R2016a using this option: options_z = ['-q -s 3 -t 2 -c ', C_param, ' -p ', epsilon, ' -g ,Kernel_scale]; I'm optimizing SVR ...
4 views

### Power calculation - categorised continuous exposure in case-control study

I have a continuous exposure that I would like to catagorise it into quantiles according to the distribution of control (i.e. 25% controls in each exposure level group). From pilot study, I know that ...
13 views

### Is feature engineering relevant at all for Random Forests?

Random forests is an ensemble of trees that learns the hidden patterns in the data. I have mostly tried doing some feature-engineering before running the Random Forest model but is it required or the ...
8 views

### Behaviour of neighbouring points in LOESS smoothing when data is not uniformly distributed

The purpose of loess is to create an 'average' value of the response for any $x$, by using points in the region of $x$ to create a local regression line. From what I understand, picking the ...
6 views

### How to decide what is the relevant group in a precsion and recall computation?

One of the most famous measurements for an information retrieval system is to compute its precision and recall. For both cases, we need to compute the number of total relevant documents and compare it ...
9 views

### For a Fisher Information matrix $I(\theta)$ of multiple variables, is it true that $I(\theta) = nI_1(\theta)$?

For a Fisher Information matrix $I(\theta)$ of multiple variables, is it true that $I(\theta) = nI_1(\theta)$? That is, if $\theta = (\theta_1, \ldots, \theta_n)$, will it be the case that the fisher ...
7 views

### WEKA / Support vector machine - does attribute have positive or negative impact?

I'm doing some machine learning with WEKA using around 20 numeric attributes to predict a true/false class. Support vector machine gives me good enough results on my data set. However, I'd also like ...
19 views

### I need help with my statistics final [on hold]

i need to know what type of test to use for the following questions 1) Does Mark’s yards relate to the temperature during the start of the game? 2) Does Mark’s year in college impact the amount ...
6 views

### What methods exist to apply inference to correlated noise in experimental results?

What resources are available for applying inference/computational statistics to correlated noise (in various scientific experiments)? My idea is this: let's say we use some apparatus (e.g. a ...
4 views

### bayesian approach to estimate weekday and weekend shoppers

I am trying to predict customer is weekend or weekday shopper. The dataset has 60% of the customers as weekend shoppers. So for new shopper I can assume they 60% likely to be weekend shoppers. Now a ...
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### How can we find the Fisher Information Matrix of a linear regression model?

Suppose we have a sequence of random variables $y_1, \ldots, y_n$ such that $y_i = \beta_0 + \beta_1 x_i + \epsilon_i$ where $\epsilon_i$ is assumed to be i.i.d. $N(0,\sigma^2)$, with $\sigma^2$ ...
5 views

### Parameter selection and k-fold cross validation

I have one dataset, and need to do cross-validation, for example, a 10-fold cross-validation, on the entire dataset. I would like to use radial basis function (RBF) kernel with parameter selection ...
2 views

### Small CFA Model with 0 Degrees of Freedom, 1.0 CFI, 0 RMSEA

Can someone please help explain this to me, as I've never encountered it when running CFA before. I ran a CFA on a simple model with 4 indicators. The initial model returned all very good fit indices ...