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Category: model selection

Introduction to Hyper-parameter Tuning: GridSearchCV and RandomSearchCV

  • October 14, 2019June 27, 2021
  • by Niranjan B Subramanian

Most of the machine learning algorithms contain a number of hyperparameters that we can tune to improve the model’s performance. The hyperparameter controls the behaviors of the algorithm and has an enormous impact on the results. […]

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Cross Validation

  • August 26, 2019June 27, 2021
  • by Niranjan B Subramanian

Cross-validation is an important evaluation technique used to assess the generalization performance of a machine learning model. It helps us to measure how well a model generalizes on a training data set. There are two main […]

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