Data Understanding and Pre-processing Quiz

What are the two key stages of Data Understanding?

• Data Mining and Data Visualization

• Data Collection and Data Analysis

• Data Assessment and Data Exploration

• Data Cleaning and Data Transformation

What is the first step in data understanding?

• Data Assessment

• Data Exploration

• Data Cleaning

• Data Preparation

Which of the following is NOT a question addressed in Data Assessment?

• What data is available?

• What format will the data be in?

• What is the target variable?

• How much data is available?

What is the purpose of Data Exploration?

• To split the dataset into training and testing sets

• To select features for the model

• To create meaningful summaries of data

• To validate the feasibility of a project

What is a common split ratio for training and testing datasets?

• 80-20%

• 70-30%

• 60-40%

• 50-50%

Which technique is used for feature selection?

• Data Transformation

• Data Cleaning

• Feature Importance

• Normalization

What is the goal of hyperparameter tuning?

• To visualize the results

• To improve model performance

• To collect more data

• To clean the dataset

What does the term 'garbage in, garbage out' imply?

• Data preprocessing is unnecessary

• The model's performance is independent of data quality

• Quality of results depends on input data quality

• Data collection is the most important step

Which of the following is a method for handling missing values?

• Removing duplicates

• Imputing with mean

• Encoding categorical data

• Normalizing data

What is normalization in data transformation?

• Scaling data to a range of [0, 1]

• Filling missing values

• Removing outliers from the dataset

• Encoding categorical variables