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Model Performance Improvement

  • Karthik Ramasubramanian
  • Abhishek Singh
Chapter

Abstract

Model performance is a broad term generally used to measure how the model performs on a new dataset, usually a test dataset. The performance metrics also play the role of thresholds to decide whether the model can be put into actual decision making systems or needs improvements. In the previous chapter, we discussed some performance metrics for our continuous and discrete cases. In this chapter, we will discuss how changing the modeling process can help us improve model performance on the metrics.

Keywords

Random Forest Search Optimization Ensemble Learning Learn Vector Quantization Random Forest Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Karthik Ramasubramanian and Abhishek Singh 2017

Authors and Affiliations

  • Karthik Ramasubramanian
    • 1
  • Abhishek Singh
    • 1
  1. 1.New DelhiIndia

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