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

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Probability one sequence of coin flips predicts another, for which P(heads) is different

This question is going to be somewhat hard to describe, but here I go. Lets say we have a dataset where 75% of it is Heads, and the other 25% of it is Tails. Next, lets say we have a "perfect" coin ...
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16 views

How to represent the sum of two linear model predictions in same unit

I have built two linear regressions independently of one another, and $Y_1$ and $Y_2$ are in the same units. I am interested in using the sum of $\widehat{Y}_1$ + $\widehat{Y}_2$ (the predictions) to ...
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9 views

Are there any open-source implementations of structured prediction methods? [on hold]

I'm currently interested in structured prediction field. I've looked around the web but haven't found any implementations of this kind of algorithms in any of languages. Have I not searched enough or ...
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17 views

How to calculate a time estimate and plot it?

I recently made a website for a game's community. The game basically has an online dragon which people can fight. Each fight chips off a little bit health. On the next encounter with the dragon, ...
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24 views

LS-SVM time series forecasting

I'm trying to forecast a time series of air passengers using LSSVM with the help of the LS-SVMLab toolbox v1.8 from http://www.esat.kuleuven.be/sista/lssvmlab/, specifically the NARX model function. ...
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2answers
48 views

Forecasting if the next number is higher or lower

how will I know (or are there any math formulas) if the next number will be higher or lower based on a given set of numbers? Like: 46,73,29,12,04,27,28,81,62 - Next number is higher or lower? I'd ...
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21 views

Normalize sum(case when..) [on hold]

In Netezza I ran the following query to make the nominal variables into binomial ones and sum them up: sum(case when c.COUNTRYCODE = 'US' then 1 else 0 end) as US ...
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11 views

Predict function in r - time series

I have built a model on my training dataset where I have used the difference of the log(Y) i.e. diff(log(Y)) as my response variable. Now if I want to use this for predicting the Y variable in my ...
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12 views

References for MMSE estimator for forecasting future value

As the title says, I have been looking for articles on minimum mean squared error (MMSE) estimator for forecasting. But so far I cannot find any. Does anyone know some articles on this subject?
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14 views

Should I use 'sample standard deviation' for 'prediction intervals' and 'standard error of the mean' for 'confidence intervals'?

I just want to make sure I am getting this right. When I am concerned about the "result" of any particular new datapoint I should use prediction intervals not confidence intervals. When I am concerned ...
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13 views

LSSVM Prediction using LS-SVMLab toolbox v1.8

I'm trying to forecast a time series of air passengers using LSSVM with the help of the LS-SVMLab toolbox v1.8 from http://www.esat.kuleuven.be/sista/lssvmlab/, specifically the NARX model function. ...
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15 views

Combining continuous spatial and discrete time series methods for spatial prediction

Here's something I've been pondering. Wondering if anyone can shed come light on it/recommend some references/tell me why it makes no sense, please. In my field (predicting crime risk by location), ...
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17 views

Estimate battery's real capacity in real time

The maximum capacity of a battery during usage can vary from manufacturer's specifications due to factors like temperatures and battery health. Because of that i want to estimate the real maximum ...
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1answer
27 views

Definition of residuals versus prediction errors?

I always thought the definition of residuals is the difference between the statistic and the observations. And, the definition ...
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1answer
27 views

Machine Learning Procedure for Fractional/Proportional Data?

I am looking for some suggestions of machine learning procedures that work to predict fraction outcomes where the outcome variables $\in [0,1]$. Can you provide me with any suggestions? I thought ...
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1answer
37 views

Predicting values from linear regression

I've got a data set consisting of olympic years and the winning times for the womens 100m. I can plot a line throught the data using matlab as such: ...
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18 views

10-fold cross validation of a Multinomial Regression Model SPSS 20.0

I have a set of 125 people that belong to one of four nominal categories. Each person is described with 7 descriptors with 2-5 nominal variables that I use in my regression model to predict the ...
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1answer
33 views

What statistical method would I need to employ to predict a school's attendance if I know previous five years' attendances?

I have attendances month by month (September-June) for a given school X for the following school years:2011-2012, 2012-2013, 2013-2014, 2014-2015. I also have the attendance for students at school X ...
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1answer
58 views

Calculating the probability a predicted point is 0

I have a deterministic function $f(x)$ and have evaluated some points $x_1,...,x_n$. So essentially I have pairs of data $(x_1,f(x_1)),...,(x_n,f(x_n))$. I am modeling the function $f(x)$ using a ...
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15 views

Estimating the battery capacity using current power consumption and battery percentage

I want to estimate the current maximum capacity (in kWh) having the current power consumption (in kWh) and the state of charge of the battery (in %) available in a time series. I do not have a full ...
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21 views

Gaps of methods to evaluate prediction accuracy

There are many methods to evaluate prediction models based in prediction errors, such as MSE, MAE, MAPE, WMAE, etc. These methods are usually used in data prediction competitions, where one is given a ...
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21 views

Aggregating estimates for weekly data

I have a data set (in R) measuring the performance of all machines in a factory at the end of one week. Each machine has various metrics captured (feature vector) and the ppm defects (predicted ...
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1answer
25 views

Metrics to asses the ability of a model to predict a probability

Problem setting Here is the problem. A customer is faced to several products corresponding to the needs he has expressed. The goal is here to predict the probability of each product to be chosen. ...
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2answers
44 views

Best statistic for measuring prediction accuracy that is robust for outliers

I have recently built a model, designed for prediction. Initially, I chose model A over B - better RMSE and better MAPE. However, after carefully evaluating each prediction on my test dataset for ...
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11 views

Does cross-validation for model selection using MSPE make sense for mixed models?

Does cross-validation for model selection using mean square prediction error make sense for mixed effect models such as produced by lme4? If so, under what conditions / caveats? Also, are there any ...
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19 views

Proof for Irreducible Error statement in ISLR page 19

This section of Introduction to Statistical Learning in R (page 19 in v6, statement 2.3) is motivating the difference between reducible and irreducible error (that is noted by $\epsilon$ and has mean ...
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7 views

Evaluating predictions consistently

I am confused about how to assess predictions I make (specifically on PredictionBook, but I believe my confusion isn't specific to PredictionBook). I'm not sure if Cross Validated is the proper place ...
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15 views

Applying an uncertainty to a prediction

I am estimating/predicting the numbers of students who will pass on an exam at a school this year. My method is very simple: Each student give me a guess of their own grade one month before the test. ...
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14 views

Inference in Bayesian network Using bnlearn package

In this link Prediction of continuous variable using "bnlearn" package in R , the author talk about how I can find the conditionl probability of P(node(C)\ the rest node)=P(C\A,B,D,E,F,G) ...
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13 views

“Cooking ingredients” problem

I have a problem like this. Suppose I have 3 persons, A,B, and C to make cookies with 3 basics ingredients, flour, egg, and water. The recipe to make cookie is unknown but we need too determine the ...
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27 views

Investigating characteristics of good prediction schemes

Short: I am evaluating prediction schemes. Using which formalized (statistical) method can I investigate what are the characteristics that differentiate the best from the worst in terms of their ...
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2answers
89 views

Using x to predict y when they are highly correlated

I am trying to use an organism's length (x) to predict weight (y), but length and weight are highly correlated (r=0.95). Are there any pitfalls I should be aware of because estimates of the two ...
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29 views

Test error of probability “prediction” for little league soccer

Background: I have multiple sets of team's little league soccer scores made up only of whole numbers [0-12 inclusive], eg: ...
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1answer
18 views

Looking for an error measure like MAE that weights overprediction more than underprediction

I am trying to evaluate my prediction results using common error measures like the MAE, MSE or RMSE. For me it is much worse if the predicted value is higher than the true value. If it is less, it is ...
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1answer
62 views

Predicting running times for track meet places

Good morning all, I'm a track/running coach in Texas. That's my gentle way of saying that I don't have a statistical background, but I'm trying to learn what I can. Forgive me if I don't use the ...
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34 views

Cross validation with model selection (in-sample fit and out-of-sample prediction)

I currently have 3 models to predict Y from a linear combination of independent variables: Model 1: Y ~ A + B Model 2: Y ~ A + C Model 3: Y ~ A + D Now, I want to compare their in-sample fitting ...
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1answer
48 views

Decompose ridge regression bias error into model bias and estimation bias

How can I show that the in-sample bias error in Ridge regression can be decomposed into model bias plus estimation bias? I.e., if $Avg$ takes the average over all the input variables $x$ in the ...
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1answer
28 views

Prediction or forecast error

I understand the general idea of different time series model fittings, calculations, and model comparison. However, I am a little confused of understanding the forecast of a time series model. For ...
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1answer
56 views

R predict function and Model Object [closed]

I'm doing machine learning in R. I would like to know how we can create a model object that we can pass to "predict" function along with new data so that we obtain predicted values. To elaborate, I'm ...
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40 views

Daily prediction using ANN in R: {neuralnet} package

Relying on fitting ANN, I've currently trained my neural network and have been glad with the results on my test set by comparing Actual vs Predicted values. Now I ...
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2answers
50 views

What ML algorithm(s) should I learn in order to predict based on multiple features the likelihood of a binary event occurring in the next week?

What ML algorithms should I learn in order to predict the likelihood of an event occurring in a specified time period from the present forward based on multiple features in historical data I've ...
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1answer
18 views

Over sampling imbalance data in SVM

Basically I have a medium size data set (20,000 observations) with only 200 being in group 1, thus an imbalanced data set. My goal is to predict as much group 1 class as possible without sacrificing ...
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1answer
34 views

How do I model seasonal patterns for underprediction?

I want to predict sales in food-vending machines (to ultimately prevent food waste). I work with scikit learn. My current models are not too bad, but they show ...
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13 views

Using known and complete data to predict data part of which is know and the rest is unknown

It is a general problem. I have a training set(size > 1000). Each data point has 1000 features. What I want to do is to use these training data to complete a data point which has 600 known features ...
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31 views

How to predict where someone will go given a history of different locations that person visited?

Title says it all. I want to predict where a person will go at time=now if we know they have a history of x unique visits at n different places. I think some relevant variables would be what hour ...
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24 views

Dimensionality reduction and dynamic weighing of large set of correlated features

This is a question on what's the right hammer for my nail. Bare with me, I'm not very experienced with machine-learning techniques yet, but need some pointers in the right direction. I have a ...
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17 views

Using Population Statistics to Predict future Population Statistics: General or Specific Demographic Groups?

I apologize in advance if I don't use the right terminology. Problem to Solve: I want to predict the voter turnout behavior of Black, Male, Non-latinos for Springfield in the upcoming election. ...
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1answer
44 views

price prediction in r using time series

I am trying to make a prediction of imbalance prices in the elctricity market. My dataset consists of data for every 15 minutes (this is the time period in which a price is determined) during 11 ...
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1answer
26 views

crossvalidation for forecasting sales

My objective is to predict the sales 6 weeks in advance. I have data that from 01-Jan-2013 to 31-June-2015. I am supposed to predict the sales from 01-Aug-2015 to 17-Sept-2015 using machine learning. ...
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2answers
42 views

Prediction Accuracy - Another Measurement than MAPE

I have the question for my prediction model, which estimates used car prices. For example: Car: 20.000 km, real price: 32.000 Euro, prediction: 27.000 Euro --> MAPE: 15,6% , absolute difference : ...