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Error Correcting Output Code

Error Correcting Output Code

Improve the reliability of predictions for multiclass codifying complications by delivering it to an ensemble of classifiers.

Bootstrap Aggregation

Used to reduce the contrast between those algorithms that have high variance thorugh a high divergent maching learning.

Bootstrap Aggregation
Boosting

Boosting

Fitting models into high weighted data and then analyzing data for errors. Selenium is integrated with tools like TestNG and JUnit for managing test cases and generating reports.

Experience Selenium

Experience the power of Selenium

Harness a more cohesive and product oriented API as well as convenient access to the API of Selenium Web drivers like Firefox, Chrome etc.

  • Learning algorithms by constructing a particular set of classifiers.
  • Classifying new data points by voting the predictions.
  • Training machine learning algorithms with the training dataset.
  • Using voting for classification and averaging for regression.
  • Focus on Importance Sampling, Model averaging and Bayesian predictions.