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 TransformWhat is a feature crossBefore being input into an ML model raw data must be turned intoWhich of these accurately describes the relationship between Apache Beam and Cloud DataflowSelect 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
