D-DS-FN-23 Exam Dumps - EMC Data Science Questions and Answers

The rug() function in R adds small tick marks along the axes of a plot to represent the distribution of a variable, effectively showing it along both axes for better visual interpretation.

The decision tree having 17 layers and a leaf node with only three customers suggests that the tree is overfitting the data. This is because a deep tree with many layers can lead to overfitting, where the model fits the training data too closely, capturing noise and small details that do not generalize well to new data. Reducing the tree depth or pruning the tree can help mitigate overfitting.

Feature selection involves identifying the most useful input variables that contribute meaningfully to the model, improving accuracy and reducing complexity during the model building phase.

Both matrix and array data structures in R can only contain one data type across all their elements, ensuring consistency in the structure.

An Excel file is an example of quasi-structured data because it contains structured data (like rows and columns) but may have irregularities, such as varying data formats, missing headers, or mixed data types within cells, making it less strictly structured than a relational database.

A box and whisker plot is ideal for visualizing the relationship between time spent and product category, especially when you have multiple categories. It shows the distribution of time spent in each product category, including the median, quartiles, and any potential outliers.

The naïve Bayes conditional independence assumption is applied to simplify the probability calculations by assuming that the features are independent given the class label. This reduces the complexity of the model and makes computation feasible even with many features.

A graph of the WSS (Within-Cluster Sum of Squares) versus the value of K helps determine the optimal number of clusters. The "elbow" point on the graph represents the value of K at which adding more clusters no longer significantly improves the WSS.

A key business driver for Big Data analytics adoption is the ability to identify new business opportunities by analyzing large and complex datasets, which can provide valuable insights for decision-making and strategy development.

A branch in a decision tree represents the outcome of a test or decision on a variable, leading to further splits or classifications based on the test result.