Data is often segmented using decision trees, with each branch splitting the data set in half or into three subsets. However, unanticipated results may occur if the decision tree is not trimmed. Talk about what pruning is, why it's done, and when it happens.

What causes algorithms to produce biased results? A) the dataset contains no data B) the programming language are wrong C) the dataset is skewed in one direction D) the programmer are inexperienced

Use decision tree to further explore the dataset, where the dependent variable is ‘smoker’. Please explain the approach taken. [No more than 300 words]

Which statement best describes k-means cluster analysis?   Question 9 options:   It is the process of organizing observations into distinct groups based on a measure of similarity or dissimilarity.   It is the process of agglomerating observations into a series of nested groups based on a measure of similarity or dissimilarity.   It is the process of reducing the number of variables to consider in data-mining.    It is the process of estimating the value of a continuous outcome variable.