Search for tag: "algorithms"
DSPA Chapter 16 (Variable Selection)DSPA Chapter 16 (Variable Selection) As we mentioned in Chapter 15, variable selection is very important when dealing with bioinformatics, healthcare, and biomedical data where we may have more…
From Tina Chang
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DSPA Chapter 12: k-Means ClusteringDSPA Chapter 12: k-Means Clustering In this chapter, we will present (1) clustering as a machine learning task, (2) the silhouette plots for classification evaluation, (3) the k-Means clustering…
From Tina Chang
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DSPA Chapter 13 Model EvaluationDSPA Chapter 13 Model Evaluation In this chapter, we will discuss (1) various evaluation strategies for prediction, clustering, classification, regression, and decision trees, (2) visualization…
From Tina Chang
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DSPA Chapter 14 Improvement of Model PerformanceDSPA Chapter 14 Improvement of Model Performance We already explored several alternative machine learning (ML) methods for prediction, classification, clustering and outcome forecasting. In many…
From Tina Chang
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DSPA Chapter 8 Decision Tree ClassificationDSPA Chapter 8 Decision Tree Classification In this chapter, we will (1) see a simple motivational example of decision trees based on the Iris data, (2) describe decision-tree divide and conquer…
From Tina Chang
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DSPA Chapter 11 Apriori Association Rule LearningDSPA Chapter 11 Apriori Association Rule Learning HTTP cookies are used to track web-surfing the Internet traffic. We often notice that promotions (ads) on websites tend to match our needs,…
From Tina Chang
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DSPA Chapter 6: k-Nearest Neighbors ClassificationDSPA Chapter 6: k-Nearest Neighbors Classification In the next several chapters we will concentrate of various progressively advanced machine learning, classificaiton and clustering techniques.…
From Tina Chang
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DSPA Chapter 7 Naive Bayes ClassificationDSPA Chapter 7 Naive Bayes Classification Please review the introduction to Chapter 6, where we described the types of machine learning methods and presented lazy classification for numerical…
From Tina Chang
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