Question : You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions. When have you completed the analytics lifecycle?
1. You have a completely developed model based on both a sample of the data and the entire set of data available. 2. You have presented the results of the model to both the internal analytics team and the business owner of the project. 3. Access Mostly Uused Products by 50000+ Subscribers results 4. You have written documentation, and the code has been handed off to the Data Base Administrator and business operations.
Correct Answer : Get Lastest Questions and Answer : Explanation: Operationalize: In Phase 6, the team delivers final reports, briefings, code, and technical documents. In addition, the team may run a pilot project to implement the models in a production environment.
Question : Consider these itemsets: (hat, scarf, coat) (hat, scarf, coat, gloves) (hat, scarf, gloves) (hat, gloves) (scarf, coat, gloves) What is the confidence of the rule (gloves -> hat)? 1. 75% 2. 60% 3. Access Mostly Uused Products by 50000+ Subscribers 4. 80%
1. a subset of the provided data set selected at random and used to initially construct the model 2. a subset of the provided data set that is removed by the data scientist because it contains data errors 3. Access Mostly Uused Products by 50000+ Subscribers 4. a subset of the provided data set selected at random and used to validate the model
Correct Answer : Get Lastest Questions and Answer : Explanation:In Phase 4, the data science team needs to develop datasets for training, testing, and production purposes. These datasets enable the data scientist to develop the analytical model and train it ("training data"), while holding aside some of the data ("hold-out data" or "test data") for testing the model. During this process, it is critical to ensure that the training and test datasets are sufficiently robust for the model and analytical techniques. A simple way to think of these datasets is to view the training dataset for conducting the initial experiments and the test sets for validating an approach once the initial experiments and models have been run.