1.1 - 8.10 - Normalized Input - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

For some predictive modeling functions, it is very important to normalize the numeric input variables; that is, to rescale them so they have a similar mean and standard deviation. If you do not normalize input variables, the effect of variables with a large magnitude or a large standard deviation may dominate the model and reduce the accuracy of its predictions.

Normalize input variables before calling the following functions:
  • Canopy
  • KMeans Functions
    • KMeans
    • KMeansPredict
  • KNN
  • Generalized Linear Model (GLM) Functions
    • GLM
    • GLMPredict_MLE
    • GLML1L2
    • GLML1L2Predict
  • Least Angle Regression (LAR) Functions
    • LAR
    • LARPredict
  • Linear Regression Functions
    • Linear Regression
    • LinRegPredict
  • Principal Component Analysis (PCA) Functions
    • PCA
    • PCAScore
  • Support Vector Machine (SVM) Functions
    • SVMSparse
    • SVMSparsePredict_MLE
    • SVMSparseSummary
    • SVMDense
    • SVMDensePredict
    • SVMDenseSummary

The MLE Scale functions are designed to make normalization easy. For an example of using Scale functions to normalize input variables, see PCA Example.