How to Build Your First Predictive Model


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This is designed for the beginner or someone new to Salford Systems’ data mining products. These videos skip over the theoretical background of each data mining product and show you how to:
• Import a dataset and select a data mining engine for model building
• Configure the basic model setup parameters
• Build a model with each core data mining product in the SPM software suite, and
• Interpret the output and model performance

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How to Build Your First Predictive Model

  1. 1. How-To Build Your First Model A publicatio n of
  2. 2. INTRO Building your first model with a new data mining tool can be intimidating. Though some of us may have some intuition for model building, it’s pretty daunting to look at the default settings, knowing you have a ways to go before you have an accurate, explainable predictive model to hand over to your boss. To make sure you’re set up for data mining success, follow these simple steps to build your first models in the SPM software suite.
  3. 3. Want to skip ahead? Here’s what we’re going to cover. IMPORT DATA 5 … Prepare 6 … Stay Organized PERFORMANCE Model Setup 8 … Select and Engine 15 … What To Look For 17 … What’s Next 9 … Analysis Type 10 … Variables 11 … Testing 12 … Control Parameters
  4. 4. IMPORT DATA We’re going to walk you through best practices for preparing and uploading your data into the SPM software.
  5. 5. PREPARE 1 Make sure your data is in a ‘flat’ file (i.e. rows x columns) 2 Make sure you understand your variable labels! If you don’t understand what your variables represent, you’re going to have a heck of a time understanding your results. Want to read the nitty gritty? Want to read the nitty gritty? Check out the complete SPM User Guide. Check out the complete SPM User Guide.
  6. 6. STAY ORGANIZED Save your data set, or sets, in one, easy-to-find folder. If you’re pulling in data from all over creation, you’re just making the process longer and more difficult to comprehend. Do yourself a favor and dedicate a directory to each data mining project you’re working on.
  7. 7. Model Setup 10 parameters to pay attention to when building a model Once you have imported your data, you need to set a few parameters (leaving most of them in default settings) before you click ‘start.’
  8. 8. RuleLearner/Model Compression Random Forests Select an Engine. Regression CART Data Binning CART Ensembles MARS TreeNet Logit GPS/Generalized Lasso
  9. 9. Classification. Regression. Logistic Binary. Unsupervised.
  10. 10. SELECT A TARGET VARIABLE AND PREDICTORS 1 You must have a target variable. 2 You should have multiple predictors. 3 You don’t need to use all of your predictors. 4 Take note of categorical vs. continuous variables.
  11. 11. SELECT A TESTING METHOD No independent testing – exploratory tree Fraction of cases selected at random for testing (%) Test sample contained in a separate file V-fold cross-validation (i.e 10)
  12. 12. Salford Systems Recommends That You Manually Set Your: • Learn rate • Number of trees built • Number of nodes in a tree • Loss criterion *These will vary depending on the modeling engine being used to build a model.
  14. 14. EVALUATING YOUR PERFORMANCE Don’t get overwhelmed by all of the fancy reporting features available in the SPM software suite. Start slow. We will show you where to begin if you are new to using SPM and just want to understand what your model means.
  15. 15. What To Look For • • • • • Mean Squared Error (MSE) R-Squared Test vs. Learn Performance Variable Performance Variable Dependence Plots (TreeNet)
  16. 16. … AND YOU’RE DONE! If you have already downloaded the SPM software, build a model! Once you’ve built your first model, start tweaking some of the control parameters we discussed. What is your best model performance so far?
  17. 17. WHAT’S NEXT? • Watch our video series on how to build your first model. Watch our video series on how to build your first model.