Big Data 3

What are the four step of preprocessing data before performing unsupervised machine learning ?

• Data translation

• Data Encoding

• Scaling

• Dimensionality reduction

• Data Basing

How can you transform categorical data ?

• By using techniques such as one-hot encoding, label encoding, or ordinal encoding.
• By using techniques such as mean encoding, mode encoding, or median encoding.
• By using techniques such as binary encoding, target encoding, or frequency encoding.

How to select the right amount of feature for a clustering algorithm ?

• By randomly selecting features
• By using the most complex features
• By not considering the features at all
• By using techniques such as dimensionality reduction, feature selection, or domain knowledge.

What is the importance of feature selection in a clustering algorithm?

• It helps in reducing the dimensionality of the data

• It helps in improving the accuracy of the clustering algorithm

• It has no impact on the clustering algorithm

• It makes the algorithm more complex

What is the bias and the variance for machine learning models ?

• Bias and variance are sources of error in machine learning models.
• Bias and variance are the only factors that determine the accuracy of machine learning models
• Bias and variance are not relevant for machine learning models
• Bias and variance are not related to error in machine learning models

What can be clustering useful for in healthcare ?

• Identifying patient groups with similar characteristics or grouping similar medical cases together
• Organizing medical records by the day of the week they were created
• Sorting patients by their favorite color
• Grouping patients by their shoe size

What is the significance of the elbow method in clustering?

• It helps in determining the optimal number of clusters

• It helps in visualizing the clusters

• It has no impact on the clustering algorithm

• It makes the algorithm more complex

What is the basic concept behind Neural Network ?

• Using quantum computing principles
• Replicating the functions of a mechanical calculator
• Simulating the functioning of the human brain using interconnected nodes.
• Storing data in a tabular format

What is reinforced learning ?

• A type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve some goal.
• A type of learning that relies on trial and error without any specific goal
• A type of learning that focuses on physical activities and hands-on experience
• A type of learning that involves memorizing facts and information