Select all the true statments for the decision trees: [scoring is right-wrong] a decision tree classifier can classify a data that is not linearly separable large decision trees can easily overfit to the data and have high variance | a single node decision tree (stump) has low variance and high bias decision trees find the global optima of their defined cost function, e.g. the misclassification cost

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Select all the true statments for the decision trees: [scoring is right-wrong]
a decision tree classifier can classify a data that is not linearly separable
) large decision trees can easily overfit to the data and have high variance
a single node decision tree (stump) has low variance and high bias
) decision trees find the global optima of their defined cost function, e.g. the
misclassification cost
Transcribed Image Text:Select all the true statments for the decision trees: [scoring is right-wrong] a decision tree classifier can classify a data that is not linearly separable ) large decision trees can easily overfit to the data and have high variance a single node decision tree (stump) has low variance and high bias ) decision trees find the global optima of their defined cost function, e.g. the misclassification cost
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