Predictive models are statistical models whose primary purpose is to predict other observations of a system optimally, as opposed to models whose purpose is to test a particular hypothesis or explain a phenomenon mechanistically. As such, predictive models place less emphasis on interpretability and ...

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Discrimination between measurements made at different points in time

I would like to ascertain what variables discriminate best between experimental conditions in a repeated-measures experimental design. I have performed Repeated Measures MANOVA to determine whether ...
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59 views

How to score predictions in test set taking into account the full predictive posterior distribution?

I have three predictive models (regressions) which parameters are estimated by Markov Chain Monte Carlo. Predictions are made over a test set of size $N$. Since I compare the models under different ...
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Incorporating intraday data into end-of-day forecast

my target variable is observable intraday but I am interested only in EOD forecasts. I will denote the variable $\ y_{D,24}$ as the reading of interest for day D is ...
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30 views

Modelling flight delays with negative values

Modelling flight delays with negative values I am working on a model to predict whether a flight will be delayed. The data consists of some explanatory variables for flights from a specific airport. ...
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Comparing the impact of 2 independent variables on the dependent

I'm using a predictive modelling technique which has 2 parameters. I've performed a sweep of values for each of these 2 parameters, running each permutation of parameters 30 times as the technique is ...
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20 views

Incorporating systematic error in (spatial) predictive modelling

I have created a model (random forest) and withheld 20%. When I apply the model to the withheld dataset and check the residuals against the real values I can see there is a systematic error e.g lower ...
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How can I use the output of KODAMA to predict unknown data points?

I can use KODAMA to create a model that classifies input data into two groups by setting the W vector to indicate the group and fix to a vector of all ...
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18 views

One-Step ahead predictive likelihood for time series forecasting

I am still new to Bayesian forecasting, so I am hoping to get some clarification on a simple concept (by the sounds of it). Suppose that we are interested in forecasting some time series one-step ...
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15 views

Predicting Arrival/Departure of butterflies

I don't have a solid background in statistics. I am double checking with you on a phenomenon I am trying to study. we are doing a study of some very rare species of flowers. We are putting them in ...
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14 views

train multiples observations from the same person in caret

I have data where persons were give four different tasks under three different conditions (intensities). The data looks like this: ...
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28 views

What predictive models allow me to make new predictions on a series in constant time, without needing to recompute previous ones?

I'm a software developer working on a system that stores thousands of independent metrics, each with several tens of thousands of timeseries data points. We'd like to make predictions about where the ...
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52 views

Overfitted Cox regression

I'm trying to compare the prediction abilities for death of two new biomarkers using a cohort of 173 patients. My problem is that I have only 31 outcomes and my baseline model (the one without any ...
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What models allow the study of the relation between a set of response variables and a set of covariates?

A first technique that comes to mind is Canonical Correlation Analysis. Bayesian Networks and other graphical models, I guess, can also be used to analyse such things. Any else that I should be aware ...
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Choosing a good binary classifier to be trained by a small set of labeled data

I have a small set of labeled data (diagnosis in individual subjects): ~50 of "sick" observations ~100 of "healthy" observations In reality, only ~1% of the observations are expected to be ...
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217 views

Deciding between a linear regression model or non-linear regression model

How should one decide between using a linear regression model or non-linear regression model? My goal is to predict Y. In case of simple $x$ and $y$ dataset I could easily decide which regression ...
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42 views

Conditional distribution for Exponential family

We have a random variable $X$ that belongs to the exponential family with p.d.f. $$ P_X(x|\boldsymbol \theta) = h(x) \exp\left(\eta({\boldsymbol \theta}) . T(x) - A({\boldsymbol \theta}) \right) $$ ...
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How to predict values? [duplicate]

I have a simple time series with at least a measurement a day. I would like to know if there are algorithms that can deal with missing values and measurements that are not taken always at the same ...
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12 views

Apply Cross Validation to a prediction linear regression model

Hello I am slightly confused on how to apply a k-fold cross validation to a prediction linear regression model. Also how can i look at the data that the prediction model outputs before i apply cross ...
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44 views

Predictive Model - Increase Pediction Accuracy for Less Likely Events

I am trying to build a model that predicts the which binary category a respondent belongs to (0 or 1). I have demographic variables (all categorical) and a few 10 point questions. I have built a few ...
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32 views

Best prediction model for binary data

I have a large medical data set (100.000+ patients), and have many variables (but selected 20 most interesting ones - 15 of these are binary). I want to make a model that predict if these patients ...
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53 views

When make clusters in a predictive glm model?

If I want to build a predictive glm model, should I make cluster analysis on 100% of observations or on training sample (80%)? Thanks
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What is the proper name of a model that takes as input the output of another model?

Thanks in advance for the help. I am writing a paper and for the life of me can't remember the proper term for a model that works as follows. ...
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42 views

Questions about weather prediction in scikit learn

Hello I am a high school student doing research on weather. I have a dataset that has four columns each labeled with time, pressure, and lat/long. I am confused on the cross validation process. What ...
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41 views

Is it better to use MAE or MSE for perfomance measure? [duplicate]

My data set is about forest fires in Portugal. I want to define a model that can predict better wildfires. In my data set, the outliers are entries referring to big fires. What is the best performance ...
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predictive modeling: comparing actual and predicted values in terms of accuracy

I have applied a predictive model on a hold out data set on which I know actual values of the target variable. I wonder how to compare actual and predicted forecasted values, verifying whether on ...
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38 views

What does it actually mean for classes to be balanced?

I saw the following statement when reading Kuhn's APM: "The classes are fairly balanced; there are 111 samples in the first class and 97 in the second..." I thought balance would require the ...
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How fair is it to use the word “predict” for (logistic) regression?

My understanding is that even regression does not give causality. It can only give association between y variable and x variables and possibly a direction. Am I correct? I've often found phrases ...
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would adding the probabilities in a dataset be more accurate than the individual results?

Say I have the titanic kaggle competition, but I'm not interested in the competition for predicting survival for each individual. Instead I want the most accurate estimate of total survivors on the ...
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56 views

Mortgage loan predictive analysis

I have hundreds of thousands of mortgage loan historic records that look like these 2 examples: ...
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60 views

How to overcome prediction results that are overestimated

I'm trying to create a prediction model for estimation of continuous variable based on about 35 Independent variables.My data set has circa 27k observartions. Here is the summary of the the targeted ...
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71 views

p value vs prediction error

In a lot of fields (like medicine) to check if a variable is related to an output is controlled if the p-value of that variable in a regression model is significant. For example: ...
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Test Error less than cross-validation error-implications?

If the test-set RMSE error of a model is less than cross-validated RMSE error, how can I interpret this? Is this abnormal? Does it imply a mistake in the methodology?
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38 views

Predicting university course marks using historic data of class mean and student's own marks

I would like to predict my course marks for this year based on the data for class mean and my own marks for the past years. What would be a good starting point for a model for such kind of data? ...
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39 views

How to compare 2 predictive models where one uses predictor with missing values

I am developing a model to predict y from a dataset (N=20,000) that contains x1, x2. Say I ...
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Finding the most relevant predictors (features) to build predictive model

I am building a predictive model using CART. I use features (X1,X2, .. X20) and Y as a target. How can I decide which are the most relevant predictors (filtering correlated and features with less ...
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57 views

optimal down payment estimation in credit scoring

Knowing I can estimate the risk of default, via logistic regression, of a consumer on a small loan... what would be the best way to estimate the optimal down-payment amount to ask for in order to ...
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How to modeling the movement of an object? [closed]

I have implemented the condensation algorithm in order to track a moving object in video sequences, so I would improve the predictive step. Currently the state includes only the coordinates of the ...
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RandomForest - why isn't it predicting well with manually-selected test sets?

I am using python sklearn.ensemble to do a RandomForestClassifier on about 800K rows of data, coupled with sklearn.cross_validation to generate the train/test sets. When it completes, it says on the ...
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60 views

Standard deviation of residuals from a linear regression

I've ran this linear regression: mtcars_lm <- lm(mpg ~ wt, mtcars) Lets say I observe a value of mpg that is 2 above the ...
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Logistic regression - how good is my model?

I am a beginner in ML so apologize in advance if this sounds silly. I did a logistic regression on a real data set and I am having problems measuring how well my model fits. I still don't understand ...
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1answer
26 views

MSEP and R2pred for Linear Model

I have two set of data 1-Training (Calibrating) 2-Test. With these datasets, I Fit the model using first dataset. predict using the second dataset x-variables I have to test the closeness of the ...
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22 views

cumulative uncertainty with time series predictive model

So I have a time-series with a set of variables a, b, c... and another measured variable y. What I do is using the initial state of a,b,c and y (at t0), I predict what y "should" be at the next time ...
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Class Imbalance

What are the best practices for fitting a binomial classification model when the classes are very imbalanced? For example, 99.9% 1's and 0.1% 0's.
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“Select All That Apply” — How To Generate a Predictive Model with this Type of Question

For a particular question in a survey, respondents have been asked to select all that apply (i.e. say from a list of books they have read). I'm wondering if anyone knows how I would be able to build ...
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43 views

Finding predictors of upper level of a variable

I am analyzing data on a health variable and its relation to age, gender, height etc. I am more interested in 90th percentile of the health variable, which can be called upper limit of 'normal'. How ...
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111 views

Multiple regression or anova or bestglm or forestplot or Boruta

I have data on a continuous health variable and following others: age, gender, height, weight, waist, city and season. I applied multiple regression and got following output: (age, gender, height, ...
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34 views

Decision Tree Modelling

Can anyone explain me about Decision tree parameters - minSplit, minBucket, Complexity, minDepth with some simple decision tree example? And how this parameters will affect the accuracy measure? ...
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84 views

Modelling Technique

I have a 5 years of Cargo insurance (goods transportation insurance) data. I need to predict the claim amount based on their policy date and some other variables like mode of transportation, Country ...
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What is the test error, if response in test set is missing?

I am given two data set: one used for train model, and one for prediction. However, there is no response variable in the second data. I was asked to test the model built from the first data on second ...