D491 Introduction to Analytics - Set 2 - Part 2

Correct Answer: To scale numerical data to a consistent range

Normalization scales numerical data to a consistent range, usually between 0 and 1, to ensure that all features contribute equally to the model.

Correct Answer: Pie chart

Pie charts are used to compare the proportions of different categories by dividing the circle into segments that represent the relative sizes of each category.

Correct Answer: Data preparation

The data preparation phase focuses on cleaning, transforming, and conditioning raw data to make it suitable for analysis.

Correct Answer: To group similar data points into clusters

Clustering algorithms are used to group data points into clusters based on their similarity, making them useful for unsupervised learning tasks.

Correct Answer: Association rules analysis

Association rules analysis is commonly used in market basket analysis to identify products that are frequently purchased together.

Correct Answer: To reduce overfitting by testing the model on multiple data subsets

Cross-validation helps reduce overfitting by splitting the data into multiple subsets and testing the model on each subset, providing a more accurate evaluation.

Correct Answer: Recall

Recall, also known as sensitivity, measures the proportion of actual positive cases that are correctly identified by the model.

Correct Answer: Scatter plot

A scatter plot is ideal for comparing the distribution of two continuous variables, as it shows the correlation between them by plotting data points on a graph.

Correct Answer: To reduce the number of input variables

Feature selection reduces the number of input variables in a machine learning model, simplifying the model and helping to avoid overfitting.

Correct Answer: Principal component analysis (PCA)

PCA is commonly used for dimensionality reduction, transforming the original features into new components that preserve most of the variance.

Correct Answer: To fill in missing data with substituted values

Imputation is used to fill in missing data points with substituted values, such as the mean, median, or mode of the feature, to ensure a complete dataset.

Correct Answer: Linear regression

Linear regression is used to predict continuous outcomes by modeling the relationship between the dependent variable and one or more independent variables.

Correct Answer: Scatter plot

A scatter plot shows the relationship between two continuous variables by plotting individual data points on a Cartesian plane, revealing any correlations.

Correct Answer: To visualize the performance of a classification model

A confusion matrix shows the performance of a classification model by displaying the number of true positives, false positives, true negatives, and false negatives.

Correct Answer: Principal component analysis (PCA)

PCA reduces the dimensionality of a dataset by transforming the original features into new components that capture most of the variance.

Correct Answer: Communicate results

The communicate results phase focuses on interpreting the analysis and sharing the findings with stakeholders to guide decision-making.

Correct Answer: Logistic regression

Logistic regression is commonly used to predict categorical outcomes, particularly binary outcomes, such as yes/no or true/false.

Correct Answer: F1 Score

The F1 Score combines precision and recall into a single metric, providing a balanced evaluation of a classification model's performance.

Correct Answer: It reduces overfitting by averaging multiple decision trees

Random forest reduces overfitting by averaging the predictions of multiple decision trees, resulting in a more robust and accurate model.

Correct Answer: Normalization

Normalization scales numerical features to a consistent range, usually between 0 and 1, ensuring that all features contribute equally to the model.