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ICT707 Big Data Assignment

tag 0 Download 9 Pages / 2,114 Words tag 04-11-2020
  • Course Code: ICT707
  • University: Stanford University
    icon is not sponsored or endorsed by this college or university

  • Country: United States


Regression models can be used to predict just about any variable of interest. A few examples include the following:

  • Predicting stock returns and other economic variables
  • Predicting loss amounts for loan defaults (this can be combined with a classification model that predicts the probability of default, while the regression model predicts the amount in the case of a default)
  • Recommendations (the Alternating Least Squares factorization model from Chapter 5, Building a Recommendation Engine with Spark, uses linear regression in each iteration)
  • Predicting customer lifetime value (CLTV) in a retail, mobile, or other business, based on user behavior and spending patterns

In the different sections of this chapter, we will do the following:

Introduce the various types of regression models available in ML

  • Explore feature extraction and target variable transformation for regression models
  • Train a number of regression models using ML
  • Building a Regression Model with Spark
  • See how to make predictions using the trained model

Investigate the impact on performance of various parameter settings for regression using cross-validation

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