COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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XGBoost is an Extreme Gradient Boosting algorithm that is optimized for boosted decision trees
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XGBoost is a logistic regression algorithm to split each feature of the data and used for classification problem
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XGBoost is a robust, flexible, scalable algorithm that uses linear regression and used for regression problems
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XGBoost is an efficient and scalable neural network architecture
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Detailed explanation-1: -Step 2: Data Cleaning Next, this data flows to the cleaning step. To make sure the data paints a consistent picture that your pipeline can learn from, Cortex automatically detects and scrubs away outliers, missing values, duplicates, and other errors.
Detailed explanation-2: -What Amazon SageMaker option should the company use to train their ML models that reduces the management and automates the pipeline for future retraining? Create and train your XGBoost algorithm on your local laptop and then use an Amazon SageMaker endpoint to host the ML model.
Detailed explanation-3: -22. A correct way to preprocess the data When performing regression or classification is. Explanation: A correct way to preprocess the data When performing regression or classification is “Normalize the data → PCA → training”.
Detailed explanation-4: -Accuracy, confusion matrix, log-loss, and AUC-ROC are some of the most popular metrics. Precision-recall is a widely used metrics for classification problems.