How do Random Forest Works?

Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution or all trees in the forest. The generalization error for forests converges as to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them.

How do Random Forest Works?

Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution or all trees in the forest. The generalization error for forests converges as to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them.

What will be the output of the following code- ProjectPro_DataScience_List = [1, 20, 3, 40, 5, 60]; ProjectPro_DataScience_List.append ([“45”,”55”]);?

On executing the above python list append function both the values will be appended at the end of the list as a single element only. When using append for python lists, regardless of whether you have a single element or multiple elements- it will be added as a single element. To confirm this you can just try to print the length of the ProjectPro_DataScience_List after executing the python list append function as shown above.

Print (“Number of Elements in the List is: len (ProjectPro_DataScience_List));

Output:

Number of Elements in the List is: 7

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