Question

Consider the process of standardizing data in decision trees. Identify the true statement among the following options regarding the standardization of data in the context of decision trees.

Answer 1

Standardization of data in decision trees involves transforming the data to have a mean of 0 and a standard deviation of 1, ensuring all features have the same scale. This helps the decision tree algorithm make accurate splits.

Step-by-step explanation:

Standardization of data in the context of decision trees is a process of transforming the data to have a mean of 0 and a standard deviation of 1. This is done to ensure that all the features (variables) have the same scale and are treated equally during the learning process.

Here's how the standardization process works:

1. Calculate the mean and standard deviation for each feature in the dataset.
2. Subtract the mean from each value of the feature.
3. Divide each value of the feature by its standard deviation.

For example, if you have a dataset with three features and you want to standardize it, you would calculate the mean and standard deviation for each feature. Then, for each value in a feature, you subtract the mean and divide by the standard deviation. This ensures that all the features have the same scale and are centered around 0, which helps the decision tree algorithm make accurate splits.