Friday, March 28, 2014

Machine Learning with Aster !

I am now working with Aster to do Machine Learning and statistics. Here are the functions you can use :
  • Approximate Distinct Count : to quickly estimates the number of distinct values
  • Approximate Percentile :  to computes approximate percentiles
  • Correlation : to determine if one variable is useful for predicting an other
  • Generalized Linear Regression & Prediction : to perform linear regression analysis
  • Principal Component Analysis : for dimensionality reduction 
  • Simple | Weighted | Exponential Moving Average : compute average with special algortihm
  • K-Nearest Neighbor : classification algorithm based on proximity
  • Support Vector Machines : build a SVM model and do prediction 
  • Confusion Matrix [Plot] : visualize ML algorithm performance
  • Kmeans : famous clustering algorithm
  • Minhash : Another clustering technic which depends on the set of products bought by users
  • Na├»ve Bayes : useful classification method especially for documents
  • Random Forest Functions : predictive modelling approaches broadly used for supervised classification learning

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