Question 1

Tess is tasked with analyzing a data set with multiple variables with various scales. To reduce the difference in scale in variables, she is following a common process called ______ to make the observations unit-free.
A) data mining
B) Euclidean distance
C) Manhattan distance
D) standardizing

Accepted Answer

Standardizing is a common process used in data analysis to make observations unit-free by rescaling the data to have a mean of 0 and a standard deviation of 1, thus reducing the differences in scale among variables.

Question 2

Which chart allows for a visual representation to determine a point where a model's predictions become less useful?
A) ROC Curve
B) Cumulative Lift Chart
C) Decile-wise Lift Chart
D) Sensitivity Measure

Accepted Answer

A Cumulative Lift Chart helps in identifying the point where a model's predictions become less useful by showing the lift over random selection across different percentiles of the data.

Question 3

Which chart is a bar chart displayed in 10 equal-sized intervals, or every 10% of the observations?
A) ROC Curve
B) Cumulative Lift Chart
C) Decile-wise Lift Chart
D) Sensitivity Measure

Accepted Answer

A Decile-wise Lift Chart divides the population into deciles (10 equal-sized intervals) and is used to display information, such as response rates or probabilities, for each decile. This makes it the correct choice for a chart displayed in 10 equal-sized intervals.

Question 4

When using PCA, all the following are disadvantages except
A) PCA results are difficult to interpret clearly.
B) components are weighted linear combinations and abstract.
C) PCA only works with numerical data.
D) PCA significantly increases the dimension of the data.

Accepted Answer

PCA (Principal Component Analysis) is actually used for dimensionality reduction, not for increasing the dimension of the data. It transforms the original variables into a new set of variables, which are the principal components of the original data. The other options (A, B, C) are considered disadvantages or limitations of PCA.

Question 5

The process of applying a set of analytical techniques for the development of machine learning and artificial intelligence is called data mining.

Accepted Answer

Data mining is the process of extracting knowledge from data by applying analytical techniques. It is used in the development of machine learning and artificial intelligence.

Question 6

The key distinction between supervised and unsupervised data mining is that the identification of the target variable is identified in supervised data mining.

Accepted Answer

In supervised data mining, the target variable (or outcome) is known and used to train the model, whereas in unsupervised data mining, the target variable is not identified, and the model seeks to identify patterns or groupings in the data without prior knowledge of the outcome.

Question 7

Common applications of unsupervised learning include dimension reduction and prediction model.

Accepted Answer

Unsupervised learning is commonly used for dimension reduction and clustering, not prediction models. Prediction models typically involve supervised learning, where the model learns from a dataset that includes input-output pairs.

Question 8

Normalization is the process that makes the numerical data independent of scale.

Accepted Answer

Normalization is a technique applied to data to scale the values to a specific range, making them independent of their original scale, which facilitates comparison and analysis.

Question 9

The Jaccard's coefficient is appropriate when it is more informative to match negative outcomes between observations.

Accepted Answer

Jaccard's coefficient is designed to measure similarity between finite sample sets, focusing on the proportion of positive matches (i.e., elements present in both sets) over the union of the sets, and does not specifically account for matching negative outcomes.

Question 10

Oversampling involves intentionally selecting more samples from one class than from other classes to adjust the class distribution of a data set.

Accepted Answer

Oversampling is a technique used to adjust the class distribution of a data set by intentionally selecting more samples from the underrepresented class(es) to balance the number of samples between classes, thereby helping to improve the performance of machine learning models on imbalanced data sets.

Question 11

A diagram that represents the information in equal-sized intervals, deciles, is called a cumulative lift chart.

Accepted Answer

A diagram that represents information in equal-sized intervals, deciles, is called a decile chart. A cumulative lift chart is used to determine the effectiveness of a predictive model by comparing it against a random selection strategy.

Question 12

In real-world situations, data sets contain many variables. If some variables are eliminated, valuable information may be lost.

Accepted Answer

Eliminating variables from a data set can result in the loss of valuable information that those variables represent, potentially affecting the accuracy and insights derived from data analysis.

Question 13

The principal component analysis (PCA) is a dimension reduction technique used to reduce variables without removing variables.

Accepted Answer

PCA reduces the dimensionality of a dataset by transforming the original variables into a new set of variables (principal components) that are linear combinations of the original variables, thus reducing the number of variables without explicitly removing any original variable.

Question 14

In Excel, Analytic Solver only provides the covariance matrix for performing principal component analysis (PCA).

Accepted Answer

Analytic Solver in Excel provides more than just the covariance matrix for performing PCA; it also offers features for data preparation, eigenvalue decomposition, and the ability to visualize and interpret the principal components among other functionalities.

Quiz 8: Introduction to Data Mining

Tess is tasked with analyzing a data set with multiple variables with various scales. To reduce the difference in scale in variables, she is following a common process called ______ to make the observations unit-free.

Which chart allows for a visual representation to determine a point where a model's predictions become less useful?

Which chart is a bar chart displayed in 10 equal-sized intervals, or every 10% of the observations?

When using PCA, all the following are disadvantages except