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Webinar Series: 3 Ways to Improve your Regression (Hands-on Component)

Event Details

Webinar Series: 3 Ways to Improve your Regression (Hands-on Component)

Time: January 20, 2016 from 10am to 11am
Location: http://hubs.ly/H01Q4b20
Website or Map: http://hubs.ly/H01Q4b20
Phone: (619) 543-8880 x109
Event Type: educational webinar series
Organized By: Lisa Solomon
Latest Activity: Jan 18, 2016

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Event Description

Webinar Series: 3 Ways to Improve your Regression

  • Case Study
  • Step-by-step
  • Hands-on option

January 20th and 27th, 10AM – 11AM PT

  • If the time is inconvenient, please register and we will send you a recording.

Click to Register


Abstract:
  • Linear regression plays a big part in the everyday life of a data analyst, but the results aren’t always satisfactory.
  • What if you could drastically improve prediction accuracy in your regression with a new model that handles missing values, interactions, AND nonlinearities in your data?
  • Instead of proceeding with a mediocre analysis, join us for this 2-part webinar series. 
  • We will show you how modern algorithms can take your regression model to the next level and expertly handle your modeling woes.
  • You will walk away with several different methods to turn your ordinary regression into an extraordinary regression!

This webinar will be a step-by-step presentation that you can repeat on your own!

Included with Registration:

  • Webinar recording
  • 30 day software evaluation
  • Dataset used in presentation
  • Step-by-step instruction for you to try at home

 

Who should attend:

  • Attend if you want to implement data science techniques even without a data science, statistical or programming background.
  • Attend if you want to understand why data science techniques are so important for forecasting.
 

Part 1: January 20 

  • We introduce MARS nonlinear regression, TreeNet gradient boosting, and Random Forests and show you how to extract actionable insight.
  • Techniques:
    • Nonlinear regression splines (via MARS): this tool is ideal for users who prefer results in a form similar to traditional regression while allowing for bends, thresholds, and other departures from straight-line methods.
    • Stochastic gradient boosting (via TreeNet): this flexible and powerful data mining tool generates hundreds of decision trees in a sequential, error-correcting process to produce an extremely accurate model.
    • Random Forests: this method combines many decision trees independent of each other and is best suited in analyses of small to moderate datasets.
 

Part 2: January 27

  • We will show you how to take these techniques even further and take advantage of advanced modeling features.
  • There will be overlap with Part 1. It is recommended to watch Part 1, but not required.
  • Techniques:
    • Stochastic gradient boosting: TreeNet plots show you the impact of every variable in your model; take it a step further by creating spline approximations to these variables and using them in a conventional linear regression for a boosted model performance!
    • Nonlinear regression splines: MARS nonlinear regression will still give you what looks like a standard regression equation, but instead of coefficients, you’ll see transformations of your original variables.
    • Modeling automation: learn how to cycle through numerous modeling scenarios automatically to discover best-fit parameters.

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