Home » Feature Engineering » Which of the following process steps are considered a best practice in predictive modeling Which of the following process steps are considered a best practice in predictive modeling Which of the following process steps are considered a best practice in predictive modeling >>> Feature Engineering 1. Question 1 Which of the following process steps are considered a best practice in predictive modeling? 1 point Feature engineering > Data Cleaning > Model Building Data Cleaning > Feature engineering > Model Building Model building > Feature engineering > Data cleaning None of the above 4. Question 4 An example of preprocessing a date feature is … 1 point Extracting the parts of the date into different columns: Year, month, day, etc. Extracting the time period between the current date and columns in terms of years, months, days, etc. Extracting some specific features from the date: Name of the weekday, weekend or not, holiday or not, etc. All of the above 2. Question 2 Feature engineering can include: 1 point Using indicator variables to isolate key information. Highlighting interactions between two or more features. Representing the same feature in a different way. All of the above 3. Question 3 A good feature typically …. 1 point Is related to the objective Is known at prediction time Both a & b None of the above Other Questions Of This Category During the training and serving phase tf TransformWhich of these accurately describes the relationship between Apache Beam and Cloud DataflowWhat is a feature crossBefore being input into an ML model raw data must be turned intoSelect ALL true statements regarding the ML EVALUATE functionFill in the blanks A good feature should be and haveWhat are some of the advantages to exploring datasets with a UI tool like Cloud DataprepWhat is one hot encodingYou are building a model to predict the number of points ("margin") by which Team A will beat Team B in a basketball game
