# Tagged Questions

25 views

### Methods / approach to improve the predictive accuracy of a logistic regression model

The situation: I have a logistic model that should predict a defect (1=defect, 0=no defect). My model uses 4 out of 14 parameters, which are significant for my ...
55 views

### Best way to visualize predictions from a linear model

Let's say I'm doing some predictive analytics and am trying to predict US GDP per month using a two or three month lag. After every month, I generate new predictions and am able to compare my ...
30 views

### Should predictive buying models change when products/prices change?

My company creates logistic regression models that predict who will buy based on 1st & 3rd party online click data. We use this to target online visitors with interventions like retargeting ads. ...
44 views

### data mining/predictive modelling methods for small data sets

I have a small timeseries dataset that has 30 records with 6 predictor variable and 1 response variable. I would like to regress my time series response with 6 predictor variables. I have been using ...
40 views

### How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
103 views

### What model should one use for this short time series?

Below I have quarterly total sales on the left (dependent variable), and a sample of the sales on the right. The two variables share a correlation of 98.7%. What model should I use to predict X? ...
96 views

### Negative values in predictions for an always-positive response variable in linear regression

I'm trying to predict a response variable in linear regression that should be always positive (cost per click). It's a monetary amount. In adwords, you pay google for clicks on your ads, and a ...
26 views

### Binary features for prediction

I have a set of relatively long (~1000) binary features with scalar values [0-10] attached to them. My aim is to write a predictor that learns to map the features to the [0-10] interval to predict new ...
28 views

### Tips when regressing growth rates

I have 20 months of Year over Year growth rates for a X independent variable and Y dependent variable. The correlation between these two variables is 0.72. I would like to predict Y using X for ...
22 views

### How do I predict a person's rank given a set of characteristics?

I'd like to predict a person's rank on a list (1 being top ranked, 50 is last -- ties are allowed, i.e., two people can occupy the #2 rank) given a set of characteristics (e.g., age, occupation, ...
33 views

### How to impute or predict a characteristic when one of the IVs in the prediction is other household members having that same characteristic?

In some data set A, we have: household id, person id, age, sex, and then a simple binary likes donuts / does not like donuts variable. In some other data set B, we ...
62 views

### Predicting for month in R

I'm trying to understand some concepts related to predictive modeling. So let's say that I have the following data sample and am trying to regress sales on ...
52 views

### Finding predictions from a linear model

I'm trying to educate myself about predictive analytics and am using R to generate a linear model with the following data. ...
30 views

### How to use LASSO with common shocks

I am trying to use LASSO for variable selection, on a balanced panel. I have a total of 14 predictors, and would like to reduce this variable space. The panel is comprised of ...
253 views

### LASSO in R for variable selection: how to choose the tuning parameter

I apologize in advance if this question is basic. I am trying to use LASSO for variable selection, with an implementation in R. I currently have 15 predictors, and looking to reduce the variable ...
57 views

### How to calculate a “Predicted line”? [duplicate]

Here is a regression realized with R ...
197 views

### When using linear regression analysis to get the fitted values of an outcome, why do the more extreme values tend to be predicted closer to the mean?

I am working on a project in which I am using several independent variables to "predict" the values of an outcome using linear regression. In R this is done quite simply as ...
68 views

### Combining two sets of principal components in a regression

My data set consists of a large number of time series of two frequencies: daily and monthly. I am interested in doing a predictive regression on a monthly and weekly basis. I am thinking of dividing ...
72 views

### Best method of calculating line of best fit / extrapolate to compensate for delays

Let's suppose there is a project which is expected to take a certain amount of time to complete. As certain jobs are done, we can quantifiably measure how much of the project has been completed at any ...
96 views

### How to include interaction terms in R/tree model?

I have read at many places that tree is good for uncovering complex dependencies among predictor variables. From Tree models in R: The recursive structure of CART models is ideal for uncovering ...
71 views

### Prediction uncertainty estimates for different kinds of models

For which kinds of supervised machine learning techniques is it possible to estimate how uncertain the model is about its predictions for given level/range of the predictor once the model is trained ...
117 views

### Explanatory variables with many zeros

I am trying to fit a linear model to a price response variable. Many of the predictor variables consist of mainly zeros. For example, one possible predictor variable is "drill holes". Not many parts ...
336 views

### How to predict new data with spline/smooth regression

Can anyone help give a conceptual explanation to how predictions are made for new data when using smooths /splines for a predictive model? For example, given a model created using ...
35 views

### Does doing predictive regression need a smaller sample size than exploring risk factors with logistic regression?

Cardiologists have a tool called EUROScore used to adjust the risk associated with performing heart surgery. It comes into play when, for example, one surgeon is recognised as being more expert and so ...
87 views

### When building a regression model using separate modeling/validation sets, is it appropriate to “recirculate” the validation data?

Suppose I've got an 80/20 split between modeling/validation observations. I've fit a model to the modeling data set, and I'm comfortable with the error that I'm seeing on the validation data set. ...
99 views

### Linear regression coefficient limitation

I have built a linear model using lm in R lm(age ~ sibsp + parch + pclass, trainset) Here ...
60 views

### High Dimensional Data, Multicollinearity, and Skewed Dependent Variable - a good approach?

I have a regression problem that has three key issues I am trying to tackle. The first is the data is a p >> n problem, e.g. I have about 1500 features but only about 150 examples. The second is that ...
134 views

### When to Log/Exp your Variables when performing Linear Regression?

I'm doing regression using Random Forests for predicting prices based on several attributes. Code is written in Python using Scikit-learn. How do you decide whether you should transform your ...
140 views

### Mean absolute percentage error (MAPE) in Scikit-learn

How can we calculate the Mean absolute percentage error (MAPE) of our predictions using Python and scikit-learn? From the docs, we have only these 4 metric functions for Regressions: ...
76 views

### Statistical tests on the revenue data of a small business

I have daily revenue data from a small business with 6 locations. The business sells food products that range from roughly \$2.00 to \$9.00, mainly to professionals. They do over a million dollars a ...
195 views

### Question about predictive bias - intercept and slope bias

I am slightly confused on how to determine a slope and intercept bias. I have an assignment where i am supposed to conduct a gender predictive validity bias analysis. However, my lab handout and the ...
164 views

### Why do categorical predictor variables in regression need to be recoded as multiple predictors?

I'm learning about machine learning using Python's library scikit learn, and in their tutorial here they mentioned about a categorical variable color which can have ...
127 views

### Why is Hedonic Regression used instead of Linear Regression

Why is Hedonic Regression used (especially in housing prices) instead of Linear Regression? There do not seem to be any libraries in Python (and R) for Hedonic regression, is it too niched a ...
157 views

### Algorithms for regression analysis which can handle large scale datasets

I am a CS undergraduate student and for my final project i developed a regression algorithm that is suited for large-scale datasets (i wouldn't say 'Big Data', but still large scale). For the final ...
22 views

### Hierachical Predictors in a Regression

Note: Mainly this question pertains to predictions from a model. If the unit of analysis of a regression (or any predictive model really) is the individual retail store and these stores are organized ...
19 views

### Calculating error bars for Excel Linear Regression [duplicate]

I've ben sent a forecast of sales from a consultancy. It uses Excel's LINEST function, taking 4 factors that seem to have affected sales in the past, and used them to make a prediction. How do I go ...
46 views

### Prediction with intervals as the independent variable

I have sample data that maps intervals to a number: [3,7] => 1 [6,8] => 2 [6,13] => 3 [7,10] => 3 [10,13] => 4 The dependent variable's values ...
357 views

### Predicting football match winner based only on the outcome of previous matches between the two teams

I'm a huge football (soccer) fan and interested in machine learning too. As a project for my ML course I'm trying to build a model that would predict the chance of winning for the home team, given the ...
151 views

### Model performance in quantile modelling

I am using quantile regression (for example via gbm or quantreg in R) - not focusing on the median but instead an upper quantile ...
89 views

### Predict 2 responses from two co-variates

I'm not quite sure how I should fit a model that has two responses. The data consists of target (x,y) co-ordinates and actual (x,y) co-ordinates. I would like to fit a model to predict a new set of ...
409 views

### Classification vs. regression for prediction of the sign of a continuous response variable

Say I want to predict whether or not a project will be profitable. In my sample data, the response variable is actually a continuous variable: the \$ profit/loss of the project. Because my ultimate ...
33 views

### Does it make sense to include higher level predictors when there is no higher level variance?

I want to test the relative importance of incident, victim and neighbourhood characteristics on the probability of a crime being reported to the police. I use a three-level random intercept logistic ...
129 views

### Predictive model for error of another model

Does it make any sense to build a regression model for a certain target variable on a certain training set. Then build a regression model for the errors of the previous model ( real values vs ...
127 views

### Modeling outliers of normal distribution

I am using a linear model to predict under-nutrition in children under 5. The common metric discussed is stunting (a binary outcome) which is defined as being more than two standard deviations away ...
215 views

### Why would predicted values be normally-distributed when the actual values are uniform?

I'm building a supervised learning model where the target variable is a uniformly-distributed continuous value ranging from 0-1 (originally a rank value from 1-38000, then scaled down to 0-1). The 20 ...
71 views

### Predictions when multiple outcomes

Background and Setting I have data of this format: on each subject the list of exposure to some subtances, some demographics and then a multiple response (whether the subject developed a disease or ...
343 views

### Regression model for predicting sales?

We sell machinery. The following is graph is an approximation of units sold over time for a particular piece of equipment1 : It starts out slow and slowly grows over time. I tried using linear ...
408 views

### Verification of a regression model

I need some guidance related to regression model verification using validation data. I am new to R-tool & statistics and trying my best to learn. I did search on internet too but I couldn't get a ...