Machine Learning Quiz

In feature scaling, what is the purpose of normalization?

• To convert data into a standard normal distribution

• To make all features have the same scale

• To remove outliers from the data

• To reduce the dimensionality of the data

Among the following option identify the one which is not a type of learning

• Semi Unsupervised Learning

• Supervised Learning

• Reinforcement Learning

• Unsupervised Learning

In Exploratory Data Analysis (EDA), what does a histogram visualize?

• Correlation between variables

• Distribution of a single variable

• Relationships between categorical variables

• Outliers in the dataset

What is the purpose of encoding categorical variables in machine learning?

• To add noise to the dataset

• To convert numerical variables into categorical ones

• To handle categorical data so that it can be used as input for machine learning models

• To remove outliers from categorical variables

What is Machine Learning?

• A computer program that learns from data

• A set of rules and instructions for a computer

• A type of computer hardware

• A way to store and retrieve information

What is the primary goal of data cleaning in the context of machine learning?

• To remove outliers from the dataset

• To make the dataset more complex

• To convert categorical variables into numerical ones

• To ensure data quality and accuracy

What is the role of outlier detection in data preprocessing?

• To remove all data points in the dataset

• To identify and handle extreme values that can negatively impact model performance

• To create synthetic outliers for model training

• To convert numerical variables into categorical ones

What is the purpose of a box plot in exploratory data analysis?

• To visualize the distribution of a variable

• To identify outliers in the dataset

• To measure the correlation between two variables

• To encode categorical variables into numerical format

What is the primary goal of unsupervised learning?

• Classification

• Regression

• Clustering

• Reinforcement learning

What is the purpose of handling missing data in a dataset?

• To remove the entire row with missing data

• To replace missing values with the mean or median of the variable

• To ignore missing data during model training

• To create synthetic data for missing values