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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21 views

prediction model [on hold]

i'am a very beginner in Machine learning I've got machine learning course and now I would like to practice it on prediction context. I need your first push and your help I would like to model a ...
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2answers
36 views

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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23 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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1answer
36 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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21 views

How to calculate PRESS and $R^2_{predicted}$ in Stata automatically [migrated]

So I have two models and I want to calculate these statistics. Is there any package to calculate them in Stata? PRESS statistic (wiki) And, if I am not mistaken. $$ R^2_{predicted} = 1 - ...
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6 views
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2answers
37 views

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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1answer
28 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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1answer
486 views

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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10 views

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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1answer
46 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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50 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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2answers
44 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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1answer
29 views

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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1answer
37 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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3answers
38 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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0answers
8 views

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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1answer
49 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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0answers
25 views

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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0answers
18 views

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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1answer
47 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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2answers
139 views

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
18 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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0answers
20 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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2answers
43 views

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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2answers
38 views

“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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1answer
36 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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1answer
93 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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22 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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2answers
80 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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0answers
8 views

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 ...
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1answer
40 views

Which performance measure to report?

I've trained a random forest regression model using boot632 resampling and the caret package. The output of the model tuning process gives a few different performance measures. ...
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1answer
15 views

Incremental improvement for boosting

By adding additional factors, will the fitting result of a boosting algo (say Ada boosting) guaranteed to be improved? From my experiment, adding additional factors could make the prediction accuracy ...
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1answer
86 views

How to handle zeros in target variable

I'm working on a college assignment in introductory statistics to try to predict a certain target variable. The variable is continuous but has a high percentage (60%) with zero values. This is not bad ...
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1answer
14 views

Prediction on Interaction Terms in Multiple Linear Model

I have created a MLR model where my predictor variables are continuous and categorical. I am interested in the interactions between the categorical variables. Let's say I have the response variable ...
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1answer
29 views

Method for solving problem with variable number of predictors (repost from Data Science)

REPOST from Data Science: I've been toying with this idea for a while. I think there is probably some method in the text mining literature, but I haven't come across anything just right... What ...
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19 views

How to add one covariate at a time, for neural network, lm, or tree models

I have about 26 dependent variables and 400 to 1200 independent variables with 18000 observations. Is there an R package for adding one variable at a time to identify the variable(s) that reduce the ...
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45 views

SVM predictions of timeseries (forex) data are shifted

I am trying to build timeseries prediction SVM (regression variety) for forex data based on lagged close data. And I am using R. Please see the simple code below and resulting graph, using e1071 ...
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2answers
52 views

How to compare predictions from MLE-based regression Vs. predictions from bayesian regression?

Say I have two linear regression models that I want to use for predictions. Linear regression: \begin{equation} \mathbf{y} \sim \mathcal{N}(\mathbf{X^Tb}, \Sigma_y) \end{equation} Bayesian linear ...
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60 views

fitting a model for time series data

Folks, I am working on time series traffic data where the waiting times are indexed over time, with 288 observations for 24 hour time period (interval of 5 minutes). I am trying to cleanse the data, ...
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1answer
114 views

I would like to analyze the data using R and Python. How to handle 10 millions records of data? [closed]

I would like to analyze the data using R and Python, and I am unable to open text file due to huge number of records. Is there any free database software to install in PC and load the data into it and ...
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1answer
96 views

Increasing sample size with bootstrap sampling

I'm trying to perform some classification analyses with a relatively small dataset (201 observations, 32 predictors). There are 8 classes in my data with unequal sample sizes ranging from 10 in the ...
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26 views

difference between confidence interval and prediction interval in the context of regression analysis and predictive modeling

When building prediction models, I always see the following concept 1) Confidence interval for regression model 2) Prediction interval 3) Confidence interval for predicted value I can understand ...
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33 views

Machine Learning Predictors Evaluation Using R

I've bee using R for predicitve analytics and here is issue: I'm trying to predict the species (categorical variables E1, E2, E3 and E4) of an animal using as predictors a set of nominal (NO1, NO2, ...
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16 views

Autoregressive model - predictive power

I have estimated a VAR (vector autoregressive) model on credit growth in STATA. I want to test its predictive power by comparing its estimated credit growth to observed credit growth (correlation ...
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1answer
65 views

Machine learning algorithm to predict next user's destination

I'm searching for a way to formulate my problem as a machine learning problem. Suppose I have a history of user's locations, and I want to predict his next location, similar to how Google Now does it ...
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56 views

Linear regression with log dependent variable

I have the following regression: $log(Y) = \alpha + \beta X + \epsilon$ with $E[\epsilon] = 0$ and $var(\epsilon) = \sigma^2$. There is no assumption on the distribution of the errors $\epsilon$. In ...
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44 views

Trying to find a classifier that will give me probability predictions between 0-1 in weka

This is the first time I've done any sort of predictive modelling and I think I've really confused myself. I have a training set of data with a column at the end that has either a 1 or a 0 in it. ...
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1answer
46 views

Are insignificant variables included in calculation of predicted probabilities?

When calculating the predicted probabilities in a logistic regression model, do we consider all the variables or just the significant ones? For eg: Let's say my model has: dependent variable Y and 3 ...
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26 views

Predicting the near-future values using an unevenly sampled time-series data

Summary Need help with predicting the near-future values using an unevenly sampled time-series data. Data is collected as events, and is converted to time series. I have tried out a few approached ...