Machine Learning: Jump on the Way to the Future, Discover Artificial Intelligence and Data Science. Maximize your Business in the Modern World Mastering Deep Learning, Python and Algorithms by Dan Phillips

Author:Dan Phillips [Phillips, Dan]
Language: eng
Format: azw3, pdf
Published: 2020-08-11T00:00:00+00:00

The decision trees typically require little effort on the part of users to prepare data.

Variational parameter relationships don't affect tree efficiency.

Cons of Decision Trees

Learners on the decision-tree will build complex trees that do not interpret the data well. It is called being over-fitted.

Decision trees may be unpredictable, since minor differences in the data may contribute to an entirely different tree being created. It is considered variation and must be minimized by techniques such as boosting and bagging.

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