Practical Data Science using Python - Decision Tree - Model Optimization using Grid Search Cross Validation

Practical Data Science using Python - Decision Tree - Model Optimization using Grid Search Cross Validation

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

Created by

Wayground Content

FREE Resource

The video tutorial explains the concept of hyperparameters in decision trees and introduces Grid Search CV with K-Fold Cross Validation as a method to optimize these parameters. It details the implementation process, including setting up the parameter grid and analyzing results. The tutorial also covers tuning multiple parameters simultaneously and evaluating the final model's performance.

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1 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What new insight or understanding did you gain from this video?

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