1766 search results for "Regression"

My take on the USA versus Western Europe comparison of GM corn

July 4, 2013
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My take on the USA versus Western Europe comparison of GM corn

A few days ago I came across Jack Heinemann and collaborators’ article (Sustainability and innovation in staple crop production in the US Midwest, Open Access) comparing the agricultural sectors of USA and Western Europe‡. While the article is titled around the word sustainability, the main comparison stems from the use of Genetically Modified crops in

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Fun with random effects in loss reserving

July 3, 2013
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Fun with random effects in loss reserving

For some time now, I’ve advocated for the view that non-life loss reserving constitutes a categorized linear regression. I’ll emphasize that the idea of a linear regression isn’t remotely novel. Further, the categorization is the de facto approach. I’m merely recognizing it and suggesting instances where a decision may be made about the optimality of

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The hat trick

July 3, 2013
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The hat trick

In his book Quantum Computing Since Democritus, Scott Aaronson poses the following question: Suppose that you’re at a party where every guest is given a hat as they walk in. Each hat has either a pineapple or a watermelon on top, picked at random with equal probability. The guests don’t get to see the fruit

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In case you missed it: June 2013 Roundup

July 3, 2013
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In case you missed them, here are some articles from June of particular interest to R users: You can create a Word document from a template and an R script with the R2DOCX package. Joe Rickert reviews books and other resources for learning about time series analysis in R. Timely Portfolio covers 15 years of history of time series...

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Predictive analysis on Web Analytics tool data

July 3, 2013
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Predictive analysis on Web Analytics tool data

In our previous webinar, we discussed on predictive analytics and basic things to perform predictive analysis. We also discussed on an eCommerce problem and how it can be solved using predictive analysis. In this post, I will explain R script that I used to perform predictive analysis during webinar. Before I explain about R script,

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Learning Time Series with R

June 27, 2013
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by Joseph Rickert Late last Saturday afternoon I was reading in my usual spot at the Dana Street Coffee House in Mt. View. A stranger walking by my table noticed my copy of Madsen’s Time Series Analysis (sitting there untouched again) said he needed to learn something about time series and asked if I could recommend a book. He...

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Fun with Fremont Bridge Bicyclists

June 27, 2013
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Fun with Fremont Bridge Bicyclists

Given the title of this post and its proximity to the Solstice, you will be disappointed to know that I am not writing about naked bicyclists. I apologize for any false hope I may have instilled in you.On October 11th, 2012, the city of Seattle, WA beg...

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Natural language processing tutorial

June 25, 2013
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Natural language processing tutorial

Introduction This will serve as an introduction to natural language processing. I adapted it from slides for a recent talk at Boston Python. We will go from tokenization to feature extraction to creating a model using a machine learning algorithm. The goal is to provide a reasonable baseline on top of which more complex natural language processing can be...

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Natural Language Processing Tutorial

June 25, 2013
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Natural Language Processing Tutorial

Introduction This will serve as an introduction to natural language processing. I adapted it from slides for a recent talk at Boston Python. We will go from tokenization to feature extraction to creating a model using a machine learning algorithm. The goal is to provide a reasonable baseline on top of which more complex natural language processing can be done, and...

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Natural Language Processing Tutorial

June 25, 2013
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Natural Language Processing Tutorial

Introduction This will serve as an introduction to natural language processing. I adapted it from slides for a recent talk at Boston Python. We will go from tokenization to feature extraction to creating a model using a machine learning algorithm. The goal is to provide a reasonable baseline on top of which more complex natural language processing can be done, and...

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