Prediction is concerned with assessing the probability of unknown values from known values and inferred relationships.

learn more… | top users | synonyms

0
votes
0answers
10 views

Predicting attrition

I am trying to build a model which will predict attrition in an organization and will also find out the key drivers which leads to employee attrition. The logic in order to derive the data is as ...
1
vote
1answer
9 views

Using Diebold-Mariano test to compare predictive errors in non-time-series?

I understand that the DM test is established for time series data, but could I still apply the test for non-time-series data? Could I simply replace the autocorvaiance part of the test statistics with ...
-2
votes
0answers
12 views

assign probabilities [on hold]

how do I assign probababilities to the other people in a segment based on the behaviour of one person? I have a database that I have created segments in based on address. I now want to identify the ...
0
votes
0answers
7 views

relationship between power means and population zscore calculations

Can one use a power mean of the ages in a room to determine the age break down of a room? Let's say you have a room full of people, by using the average age and standard deviation of the age, how do ...
1
vote
0answers
21 views

Prediction modeling for unbalanced and repeated data?

The following data is about virtual driving tests (t1, t2, t3) either theory (T) or Practically (P). This data is stored from online system. I am trying to develop a real-time system that will predict ...
0
votes
1answer
13 views

What is the difference between the standard errors calculated by predict.lm() and summary.lm()

I am trying to calculate standard errors of group means for a two-way-anova. I found two ways to do this (predict.lm(, se = T) and ...
0
votes
0answers
6 views

Why NRI yields different result for different forms of variate while AUC are the same? [on hold]

I am trying to find a marker to assess the predictive value for univariate Cox model. Then I tried continuous NRI (net reclassification index) and time-dependent AUC. I checked the predictive value ...
0
votes
0answers
12 views

Technology Acceptance Models can be used for prediction?

I am planing to conduct a survey to predict the adoption of Mobile Banking service in the country where it was not introduced before. I am wondering whether it is possible to apply the Technology ...
0
votes
0answers
24 views

Prediction Interval for a Zero Inflated Model

I am not a statistician. So any help is appreciated. I am modeling the cost with many. The predictors are 2 categorical variables V1 and V2. The non-zero cost form a Gamma distribution. I considered a ...
0
votes
0answers
6 views

Updating model parameters online on test data

I learn the parameters of a temporal model (in my case, an RTRBM) on some training sequences using mini-batch gradient descent. Let's say now that I am updating my model online after every prediction ...
0
votes
0answers
16 views

implementation of Poisson regression [duplicate]

I am trying to work with Poisson regression. I came across this video which is very helpful - https://www.youtube.com/watch?v=HntUY8SsYZg. In the video one of parameters (Race) is categorical and ...
1
vote
0answers
10 views

How can I determine if there is a effect relation between variables if the cause is delayed with respect to the efect?

I have a dataset from a process in which one of the variables codifies an event that I want to explain using the rest of the dataset. The problem is that the relation of the variables with the event ...
4
votes
1answer
50 views

Evaluate posterior predictive distribution in Bayesian linear regression

I'm confused on how to evaluate the posterior predictive distribution for Bayesian linear regression, past the basic case described here on page 3, and copied below. $$ p(\tilde y \mid y) = \int ...
0
votes
1answer
23 views

How much prediction accuracy of SVM (or other ML models) depend on the way features are encoded?

Suppose that for a given ML problem, we have a feature which car the person possesses. We can encode this information in one of the following ways: Assign an id to each of the car. Make a column ...
0
votes
1answer
16 views

Techniques to deal with unobserved values in test [duplicate]

In my data, I have some items that a customers purchase. I need to predict the customers behavior with different items. But in the test set, there are some items that are not present in the training ...
1
vote
0answers
13 views

Estimating the opinion of a user by looking at opinions of other users

First of all, a bit of background: i am not a statistics expert but i am an enthusiast about data analysis. I have this list of "items" and for each item i have a list of "users" and the vote that ...
0
votes
0answers
61 views

Calculate PLS Xscores for predicting new data

I wish to extract Partial Least Squares (PLS) components to apply non-linear regression (Gaussian Process Regression (GPR)) on the scores of the predictors (Xscores). The reason is my data is very ...
3
votes
0answers
53 views

How to avoid an overfitting?

The standard way to avoid an over-fitting is to use a "validation set". It means that we split the data into two parts. The first part we use to fit (train) and the second part we use to validate. ...
0
votes
0answers
6 views

Divide Feature space into regions where distribution of response variable is as different as possible?

I am trying to divide a feature space with 7 variables in regions where the distributions of a response variable are as different as possible. I have been using Earth Mover's Distance as the distance ...
1
vote
0answers
23 views

Validate predictive power of Cox proportional hazards for individual observations

Note I've edited the example to be more intuitive and closer to my real data Intro I've got data on customers purchases and with it am trying to predict which customers are more likely to make next ...
1
vote
0answers
21 views

How to evaluate double seasonal Holt-Winters model dshw?

I wanna use the dshw method from the R forecast package to predict electricity consumption. I tried to use it on the ...
1
vote
0answers
17 views

Regression involving multiple measurements on known values (calibration)

Suppose I have two continuous variables Y and X and I want to predict a Y value given a specific X value. However, the dataset I have is composed of 15 particular Y values (that are known values) ...
1
vote
2answers
15 views

Motion analysis, taking in account history

In what branch of statistics should I look into in order to extract value from motion data? Are there any models that can take up position history in order to interpolate or extrapolate future ...
0
votes
1answer
38 views

problems in doing logistic regression with unbalanced sample, give me some references

I have a dataset with lots Y=0 and few Y=1. I have to run logistic regression, so I'm using a retrospective sample in order to get a more balanced sample. Could someone give me some references that ...
1
vote
0answers
15 views

Prediction model on hybrid data

I am currently working with a data set where I have both continuous, discrete and categorical (without any order) data. And I have to predict a continuous data. To be concrete, my problem is a ...
3
votes
0answers
62 views

How to use information about likelihood of classes in a classifier?

General question: How can information about the likelihood of classes be used to improve a classifier? Suppose that the probability of each class is known quite precisely (from a very large sample), ...
1
vote
0answers
39 views

Stata vs. R survival differences; weibull scale is different, problems predicting manually

I am trying to do some survival analysis in R and as a starting point, I want to make sure I can replicate a previous analysis. I notice differences and I will demonstrate them here. I feel like there ...
3
votes
1answer
75 views

What is “Prediction Accuracy (AUC)”, and how is it the number conducted in Machine Learning?

Here is the link in question: http://applymagicsauce.com/documentation.html When the Cambridge University Psychometric Center's "Apply Magic Sauce" defines how their ...
1
vote
1answer
42 views

How could the predictive mean in a GP become negative when both the prior and the training target values are non-negative?

I am training a Gaussian process regression where the training target values are between 0 and 1 and the prior mean is the fixed zero function. The predictive mean sometimes becomes negative e.g. ...
8
votes
2answers
110 views

Regression results have unexpected upper bound

I try to predict a balance score and tried several different regression methods. One thing I noticed is that the predicted values seem to have some kind of upper bound. That is, the actual balance is ...
0
votes
0answers
20 views

Predicted Probabilities changing in non-linear way

As you can hopefully see from my code, I am trying to create profiles for prediction against a dependent variable of Voting which is yes or No binary. As you can see, the only thing I have allowed to ...
0
votes
1answer
26 views

Prediction vs. Classification in neural networks

I am learning the backpropagtion algorithm, and would like to clarify some concepts. Suppose my training data set consists of 20-dimensional bit strings that are classified into 5 different classes. ...
1
vote
0answers
31 views

Best approach to predict significant factors without any complete cases

I have a dataset that contains records of donors with various biographical info (city, state, zip, number of children) and the total amount they donated over 10 years. Some never donated and thus the ...
0
votes
0answers
7 views

Penalize a long-form panel linear regression prediction?

What is the recommended penalty, if any, for a long-form panel when calculating multiple linear regression $\hat\beta$ parameters or predicting single responses from (unobserved) values of $X_i$ in ...
1
vote
1answer
74 views

Explain “validation” process of repeated k-fold cross-validation?

My understanding is currently that the canonical repeated k-fold cross-validation (CV) process might do the following if $n=100$ observations in sample, $k=5$ folds, $i= 10$ iterations (see iteration ...
0
votes
0answers
56 views

Model averaging predictions from lmer models

I am trying to model average predictions (not betas) and estimate confidence intervals from linear mixed models run with lme4::lmer. I have experimented with functions in the MuMIn and AICcmodavg ...
0
votes
1answer
16 views

Estimate linear regression paramaters with chain modeling for longitudinal data?

Within a frequentist, deterministic paradigm of multiple linear regression, is there a (standard) method to accomplish "chain modeling for panel data" in a way that avoids formal identity (and/or ...
1
vote
0answers
61 views

Suitable graph to compare predicted and actual values across multiple sites

I would like to make a graph to compare predictions with actual values. The graph must be independent of scale and show equal emphasis for over and under prediction. The purpose is to summarise ...
0
votes
0answers
11 views

How do i get prediction accuracy when testing unknown data on a saved model in Scikit-Learn?

i have a model i have trained for binary classification, i now want to use it to predict unknown class elements. ...
0
votes
1answer
39 views

R: Comparing predictive power

I would like to compare predictive power of large number of models- +/- 50. I itended to use the ttrTests package and SPA, but I was not able to install that one since it was removed from CRAN. ...
1
vote
1answer
28 views

Understanding Model Credibility with True/False Positive/Negative

I am currently going through a tutorial with regards to a evaluation for a Logistic Regression Model in regards to Bike Buyers (Microsoft Azure) For the scored Model the True/False Positive/Negative ...
0
votes
0answers
6 views

Comparison of two entities based on samples

Suppose I have two sample sets $X = [[x_1, y_1], [x_2, y_2], ...]$ and $Y = [[x_1, y_1], [x_2, y_2], ...]$ data set $x$ points may not the same, also y values change wrt other factors/parameters lets ...
0
votes
0answers
18 views

Can auto-predicted values ever improve linear regression?

You want to predict values of $y$ using a linear model of the following form: $ y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3$ $y$ is significantly dependent upon all three variables. ...
0
votes
0answers
16 views

On the prediction mean square error of a model

Suppose my model is $y_t = \alpha + \beta t + \epsilon_t$ the l-step-ahead prediction is given by $\hat{y}_{T+l | T} = a + b(T + l)$ where $a$ and $b$ are the OLS estimators of $\alpha$ and $\beta$. ...
1
vote
1answer
55 views

making predictions with log-log regression model

Is it necessary to exponentiate the predicted values in a log-log regression model? For example my model is: $\log(y) = \log(x)$ $\log(y) = -0.5141 + 0.5377 \log(x)$ if I wanted to make a ...
1
vote
0answers
5 views

Confidence interpretation from false negative rate

For my research I'm using a tool called seeSUMO, which predicts sumoylation sites in a protein based on sequence features. When it reports your results, it gives you a level of confidence for each ...
0
votes
0answers
43 views

How to prove that Innovations in the Innovation Algorithm are uncorrelated?

I tried to search on the internet but could not find a proof... For the innovation algorithm, I am refering to the one used in the time series analysis to predict unknow value.
0
votes
1answer
23 views

I was expecting 0 and 1 as an answer of a predict function in r

I'm doing a binomial family with method="glm" in train function (caret package) and as result I'm getting predicted numbers like "0.62325028 0.51807017 0.67119878 ..." and I was expecting vector ...
1
vote
1answer
64 views

Diebold-Mariano test for predictive accuracy

I am using the Diebold-Mariano test in the forecast package of R to test the predictive accuracy. In particular, I want to ...
0
votes
0answers
8 views

Using different sets of binary indicators based on another indicator - R, linear regression

I'm trying to come up with a prediction model for an output based on the hour of the day. I already have a simple model that predicts the output based on 23 factors that represent each hour of the day ...