Data Mining

In data mining, what is the primary purpose of the Knowledge Discovery process?

• To make data storage more efficient

• To extract valuable insights from data

• To prevent data breaches

• To create data visualizations

Is classification an example of supervised or unsupervised technique?

• Supervised

• Unsupervised

Answer explanation

Classification is a type of supervised learning technique. In supervised learning, the model is trained using labeled data, i.e., we have the input data along with the corresponding output. The model learns from this data and then uses this learning to classify new observations. Therefore, the correct answer to the question is 'Supervised'.

Which of the following predictive modelling technique works for continuous values?

• Classification

• Regression

Sophia, Matilda, and Isla are working on a project to improve product placement in supermarkets. Which of the following techniques should they use to achieve this?

• Association analysis

• Anomaly detection

Answer explanation

Association analysis is the correct technique for Sophia, Matilda, and Isla to use in their project. This method is used to uncover the relationships between items, which is ideal for improving product placement in supermarkets. It helps to identify items that are frequently bought together, thus guiding effective product placement.

In the context of classification, what is the primary purpose of a confusion matrix?

• Measure the distance between data points

• Identify outliers in the data

• Evaluate the performance of a classification model

Answer explanation

In the context of classification, the primary purpose of a confusion matrix is to evaluate the performance of a classification model. It helps in understanding the effectiveness of the model by comparing its predictions with the actual outcomes, thus highlighting the correct and incorrect predictions made by the model.

If we have to find the flower species based on the petal and sepal dimensions, which data mining technique should we employ?

• Regression

• Classification

A cosmetics company wants to provide vouchers to customers based on how frequent the customers purchase the company's products. Which of the following data mining technique would be more suitable to profile customers?

• Clustering

• Anomaly detection

• Association rules

• Dimensionality reduction