APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
An ad tech company is using an XGBoost model to classify its clickstream data. The company’s Data Scientist is asked to explain how the model works to a group of non-technical colleagues.What is a simple explanation the Data Scientist can provide?
|
|
XGBoost is an Extreme Gradient Boosting algorithm that is optimized for boosted decision trees
|
|
|
XGBoost is a logistic regression algorithm to split each feature of the data and used for classification problem
|
|
|
XGBoost is a robust, flexible, scalable algorithm that uses linear regression and used for regression problems
|
|
|
XGBoost is an efficient and scalable neural network architecture
|
Explanation:
Detailed explanation-1: -A machine learning pipeline is the end-to-end construct that orchestrates the flow of data into, and output from, a machine learning model (or set of multiple models). It includes raw data input, features, outputs, the machine learning model and model parameters, and prediction outputs.
There is 1 question to complete.