328 search results for "evaluation"

Automatic Hyperparameter Tuning Methods

July 20, 2012
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At MSR this week, we had two very good talks on algorithmic methods for tuning the hyperparameters of machine learning models. Selecting appropriate settings for hyperparameters is a constant problem in machine learning, which is somewhat surprising given how much expertise the machine learning community has in optimization theory. I suspect there’s interesting psychological and

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A weighting function for ‘nls’ / ‘nlsLM’

July 19, 2012
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A weighting function for ‘nls’ / ‘nlsLM’

Standard nonlinear regression assumes homoscedastic data, that is, all response values are distributed normally.  In case of heteroscedastic data (i.e. when the variance is dependent on the magnitude of the data), weighting the fit is essential. In nls (or nlsLM of the minpack.lm package), weighting can be conducted by two different methods: 1) by supplying

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2nd CFP: the 10th Australasian Data Mining Conference (AusDM 2012)

July 10, 2012
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2nd CFP: the 10th Australasian Data Mining Conference (AusDM 2012)

The Tenth Australasian Data Mining Conference (AusDM 2012) Sydney, Australia, 5-7 December 2012 http://ausdm12.togaware.com/ The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. This year’s conference, AusDM’12, co-hosted … Continue reading →

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Preview of functional programming syntax for futile.paradigm 2.1

July 9, 2012
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Preview of functional programming syntax for futile.paradigm 2.1

I’m developing a streamlined syntax for the next release of futile.paradigm. While this version is backwards compatible, it introduces a …Continue reading »

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Network Visualization of Key Driver Analysis

July 8, 2012
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Network Visualization of Key Driver Analysis

Whatever happened to those evaluations that your airline asked you to complete after taking a flight? They ask you for a number of ratings about buying your ticket, attributes of the plane, the service you received, and if you were satisfied, if you wo...

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Solving mastermind with R

June 29, 2012
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In my last post I have shown a solution to classical sorting problem in R. So I thought that this time it would be nice to generate a strategy for playing Mastermind using R.It was shown by D.E. Knuth that Mastermind code can be bro...

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Optimal sorting using rpart

June 24, 2012
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Optimal sorting using rpart

Some time ago I read a nice post Solving easy problems the hard way where linear regression is used to solve an interesting puzzle. Following the idea I used rpart to find optimal decision tree sorting five elements.It is well known that...

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Classifying the UCI mushrooms

In my last post, I considered the shifts in two interestingness measures as possible tools for selecting variables in classification problems.  Specifically, I considered the Gini and Shannon interestingness measures applied to the 22 categorical mushroom characteristics from the UCI mushroom dataset.  The proposed variable selection strategy was to compare these values when computed from only edible mushrooms...

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PDF slides and R code examples on Data Mining and Exploration

June 4, 2012
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PDF slides and R code examples on Data Mining and Exploration

by Yanchang Zhao, RDataMining.com There are some nice slides and R code examples on Data Mining and Exploration at http://www.inf.ed.ac.uk/teaching/courses/dme/, which are listed below. PDF Slides: - Overview of Data Mining http://www.inf.ed.ac.uk/teaching/courses/dme/2012/slides/datamining_intro4up.pdf - Visualizing Data http://www.inf.ed.ac.uk/teaching/courses/dme/2012/slides/visualisation4up.pdf - Decision trees http://www.inf.ed.ac.uk/teaching/courses/dme/2012/slides/classification4up.pdf … Continue reading →

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Selection in R

June 1, 2012
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The design of the statistical programming language R sits in a slightly uncomfortable place between the functional programming and object oriented paradigms. The upside is you get a lot of the expressive power of both programming paradigms. A downside of this is: the not always useful variability of the language’s list and object extraction operators. Related posts:

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