Blog Archives

Predicting Titanic deaths on Kaggle VII: More Stan

October 4, 2015
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Two weeks ago I used STAN to create predictions after just throwing in all independent variables. This week I aim to refine the STAN model. For this it is convenient to use the loo package (Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian...

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Predicting Titanic deaths on Kaggle VI: Stan

September 19, 2015
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It is a bit a contradiction. Kaggle provides competitions on data science, while Stan is clearly part of the (Bayesian) statistics. Yet after using random forests, boosting and bagging, I also think this problem has a suitable size for Stan, which I un...

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Predicting Titanic deaths on Kaggle V: Ranger

September 6, 2015
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Predicting Titanic deaths on Kaggle V: Ranger

In two previous posts (Predicting Titanic deaths on Kaggle IV: random forest revisited, Predicting Titanic deaths on Kaggle) I was unable to make random forest predict as well as boosting. Hence when I read about an alternative implementation; ranger&n...

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Predicting Titanic deaths on Kaggle IV: random forest revisited

August 23, 2015
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Predicting Titanic deaths on Kaggle IV: random forest revisited

On July 19th I used randomForest to predict the deaths on Titanic in the Kaggle competition. Subsequently I found that both bagging and boosting gave better predictions than randomForest. This I found somewhat unsatisfactory, hence I am now revisi...

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Predicting Titanic deaths on Kaggle III: Bagging

August 9, 2015
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Predicting Titanic deaths on Kaggle III: Bagging

This is the third post on prediction the deaths. The first one used randomforest, the second boosting (gbm). The aim of the third post was to use bagging. In contrast to the former posts I abandoned dplyr in this post. It gave some now you see now you ...

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Predicting Titanic deaths on Kaggle II: gbm

July 26, 2015
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Predicting Titanic deaths on Kaggle II: gbm

Following my previous post I have decided to try and use a different method: generalized boosted regression models (gbm). I have read the background in Elements of Statistical Learning and arthur charpentier's nice post on it. This data ...

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Predicting Titanic deaths on Kaggle

July 19, 2015
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Predicting Titanic deaths on Kaggle

Kaggle has a competition to predict who will die on the famous Titanic 'Machine Learning from Disaster''. It is placed as knowledge competition. Just up there to learn. I am late to the party, it has been been for 1 1/2 year, to end by end 2015. It is ...

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More on causes of death in Netherlands over the years

July 5, 2015
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More on causes of death in Netherlands over the years

Last week I had a post 'Deaths in the Netherlands by cause and age'. During creation of that post I made one plot which I had not shown. It shows something odd. There is a vertical striping. Hence mortality varies by year across age.To examine this phe...

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Deaths in the Netherlands by cause and age

June 28, 2015
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Deaths in the Netherlands by cause and age

I downloaded counts of deaths by age, year and mayor cause from the Dutch statistics site. In this post I do some plots to look at causes and changes between the years.Data Data from CBS. I downloaded the data in Dutch, hence the first thing to do...

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SAS PROC MCMC example 12 in R: Change point model

June 21, 2015
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SAS PROC MCMC example 12 in R: Change point model

I restarted at working my way through the PROC MCMC examples. The SAS manual describes this example: Consider the data set from Bacon and Watts (1971), where  is the logarithm of the height of the stagnant surface layer and the covariate...

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