491 search results for "evaluation"

Recruiting Analysts for dynamic cutting edge public sector team

October 3, 2015
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Recruiting Analysts for dynamic cutting edge public sector team

The jobs Within the New Zealand Ministry of Business, Innovation and Employment, the Sector Trends team has recently secured resourcing for additional analysts on a range of statistical programmes. That’s the team that I usually manage, although for the next few months I’m doing a stint on a similar team, different topics. The formal details and position descriptions...

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A Simpler Explanation of Differential Privacy

October 2, 2015
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A Simpler Explanation of Differential Privacy

Differential privacy was originally developed to facilitate secure analysis over sensitive data, with mixed success. It’s back in the news again now, with exciting results from Cynthia Dwork, et. al. (see references at the end of the article) that apply results from differential privacy to machine learning. In this article we’ll work through the definition … Continue reading...

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Notes on Multivariate Gaussian Quadrature (with R Code)

September 25, 2015
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Notes on Multivariate Gaussian Quadrature (with R Code)

Statisticians often need to integrate some function with respect to the multivariate normal (Gaussian) distribution, for example, to compute the standard error of a statistic, or the likelihood function in of a mixed effects model. In many (most?) useful cases, these integrals are intractable, and must be approximated using computational methods. Monte-Carlo integration is one

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How do you know if your model is going to work?

September 22, 2015
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How do you know if your model is going to work?

Authors: John Mount (more articles) and Nina Zumel (more articles). Our four part article series collected into one piece. Part 1: The problem Part 2: In-training set measures Part 3: Out of sample procedures Part 4: Cross-validation techniques “Essentially, all models are wrong, but some are useful.” George Box Here’s a caricature of a data … Continue reading...

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How do you know if your model is going to work? Part 4: Cross-validation techniques

September 22, 2015
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How do you know if your model is going to work? Part 4: Cross-validation techniques

by John Mount (more articles) and Nina Zumel (more articles). In this article we conclude our four part series on basic model testing. When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it's better than the models that you rejected? In this...

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How do you know if your model is going to work? Part 4: Cross-validation techniques

September 21, 2015
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How do you know if your model is going to work? Part 4: Cross-validation techniques

Authors: John Mount (more articles) and Nina Zumel (more articles). In this article we conclude our four part series on basic model testing. When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it’s better than the models that … Continue reading...

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Predicting creditability using logistic regression in R: cross validating the classifier (part 2)

September 15, 2015
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Predicting creditability using logistic regression in R: cross validating the classifier (part 2)

Now that we fitted the classifier and run some preliminary tests, in order to get a grasp at how our model is doing when predicting creditability we need to run some cross validation methods.Cross validation is a model evaluation method that does not use conventional fitting measures (such as R^2 of linear regression) when trying to evaluate the model....

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How do you know if your model is going to work? Part 3: Out of sample procedures

September 14, 2015
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How do you know if your model is going to work? Part 3: Out of sample procedures

Authors: John Mount (more articles) and Nina Zumel (more articles). When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it’s better than the models that you rejected? In this Part 3 of our four part mini-series “How do … Continue reading...

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C5.0 Class Probability Shrinkage

September 14, 2015
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C5.0 Class Probability Shrinkage

(The image above has nothing do to with this post. It does, however, show the prize that my daughter won during a recent vacation to Virginia and how I got it back home). I was recently asked to explain a potential disconnect in C5.0 between the class probabilities shown in the terminal nodes and the values generated...

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From SPSS to R: eoda offers assessment for SPSS users

September 10, 2015
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From SPSS to R: eoda offers assessment for SPSS users

For a long time, SPSS has been presumed to be the standard tool for statistical data analysis in companies and public institutions. Now, more users are considering changing their programming language to R – the promising solution in regard to data mining and predictive analytics. R warrants the availability of current data analysis methods because

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