# Tagged Questions

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### 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 ...
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### 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: ...
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### 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 ...
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### 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 ...
2answers
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### 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 ...
1answer
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### 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 ...
1answer
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### 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 ...
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### 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 ...
0answers
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### 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 ...
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### 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 ...
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### Predicting Football match winners based only on previous data of same match

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 ...
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### 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 ...
1answer
87 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 ...
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### How to draw a random sample from distribution of prediction?

For my microsimulation, I want to use R to predict values and draw a random sample based on this prediction. To clarify my point: I want to simulate the number of chronic conditions people suffer ...
2answers
183 views

### How to predict shares?

Lets say I know what is the overall budget for some units and I want to predict share of budget each unit will get. I have historical data and could do regression analysis. Is it better to predict ...
2answers
534 views

### How do you apply a linear regression built in SPSS to new data and generate prediction intervals

I am trying to use SPSS to build a linear regression on historical data (dependent and independent variables) and then apply this to new data (independent variables only) to generate predicted values ...