1555 search results for "regression"

Predict User’s Return Visit within a day part-2

October 22, 2012
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Predict User’s Return Visit within a day part-2

Welcome to the second part of the series on predicting user’s revisit to the website. In my earlier blog Logistic Regression with R, I discussed what is logistic regression. In the first part of the series, we applied logistic regression to available data set. The problem statement there was whether a user will return in

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Predict User’s Return Visit within a day part-1

October 22, 2012
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Predict User’s Return Visit within a day part-1

In my earlier blog, I have discussed about what is logistic regression? And how logistic model is generated in R? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict whether a user will return on website in next 24 hours. This

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Soccer is all about money (?) – Part 2: Simple analyses

October 18, 2012
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Soccer is all about money (?) – Part 2: Simple analyses

Alright, now we have all the data we need in one dataframe. To make this code work, I assume you ran the code from Part 1. We need the dataframe big.tab.All the data presented here is based on the data from 18/10/2012. You can run an analysis with the actual data or I can do it at...

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Vendor news: TIBCO’s proprietary R runtime; Teradata’s appliance integrates R

October 17, 2012
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Vendor news: TIBCO’s proprietary R runtime; Teradata’s appliance integrates R

In a webinar today previewing Spotfire 5 (scheduled for release this November), TIBCO announced that it will include TERR: The Tibco Enterprise Runtime for R. TERR is a closed-source reimplementation of the R language engine, and not based on the GPL-licensed R project from the R Foundation. Here's the relevant slide from the webinar: By making the TERR engine...

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What a nice looking scatterplot!

October 15, 2012
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What a nice looking scatterplot!

This week, we look at plotting data using scatterplots. I'll definitely have a post on other ways of plotting data, like boxplots or histograms.Our data from last week remains the same:First, a quick way to look at all of your continuous variables at once is just to do a plot command of your data....

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Color Palettes in HCL Space

October 12, 2012
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Color Palettes in HCL Space

This is a quick follow-up to my previous post about Color Palettes in RGB Space. Achim Zeileis had commented that, perhaps, it would be more informative to evaluate the color palettes in HCL (polar LUV) space, as that spectrum more accurately describes how humans perceive color. Perhaps more clear trends would emerge in HCL space,

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Revolution Newsletter: September/October 2012

October 11, 2012
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The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full September/October edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. New R Courses Announced: Two new courses presented by Bob Muenchen (author of R...

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Age-Period-Cohort models and the decline of violence

October 9, 2012
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Age-Period-Cohort models and the decline of violence

Ever since the end of the Mexican Revolution and the Cristero War violence in Mexico inched down in fits and starts from a high of about 60 homicides per 100,000 people to its lowest level sometime during the middle of the last decade (there's some uncertainty about the number of homicides in...

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Product revenue prediction with R – part 2

October 8, 2012
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Product revenue prediction with R – part 2

After development of predictive model for transactional product revenue -(Product revenue prediction with R – part 1), we can further improvise the model prediction by modifications in the model. In this post, we will see what are the steps required for model improvement. With the help of a set of model summary parameters, the data

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Product revenue prediction with R – part 3

October 8, 2012
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Product revenue prediction with R – part 3

After development and improvement  of predictive model with R (as in the previous blog), I have focused here about making a prediction with the R model ( linear regression model ) and comparison with the Google prediction API model. In statistical modeling, R will calculate intercept and variable coefficients to describe the relationship between a

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