Machine Learning Algorithms

Ibmdbpy is a wrapper for machine learning algorithms that are available in dashDB/DB2. Currently, the following machine learning algorithms are available in ibmdbpy: K-means, Naive Bayes, and Association Rules. dashDB/DB2 supports several other data mining algorithms so this list may be extended in the future. This page contains documentation of the machine learning algorithms that are currently available.

• K-means clustering
  • Initiate clustering
    • Create a K-means object
    • Get parameters
    • Set parameters
  • Fit and predict
    • fit
    • predict
    • fit_predict
  • Explore result
    • describe
    • get labels
    • _retrieve_KMeans_Model
• Naive Bayes Classification
  • Initiate model
    • Create NaiveBayes object
    • Get parameters
    • Set parameters
  • Fit and predict
    • fit
    • predict
    • fit_predict
  • Explore result
    • describe
    • get labels
    • _retrieve_NaiveBayes_Model
• Association Rules Mining
  • Initiate model
    • Create an AssociationRules object
    • Get parameters
    • Set parameters
  • Fit, prune and predict
    • fit
    • prune
    • predict
    • fit_predict
  • Explore result
    • describe
    • _retrieve_AssociationRules_Model