Question 1:

Provide a 5-section summary report (no less than 250 words per section) on the following alternative classifiers:

1. Rule-based classifiers
2. Nearest Neighbor Classifier
3. Naïve Bayes Classifier
4. Support Vector Machines
5. Ensemble Methods

For each classifier, provide the classifier name (note: use the classifier name as a sub-header in bold font), provide the definition along with a brief explanation of the classifier (i.e. how it works), the advantage and disadvantage of using the classifier, and provide a data example of its use (i.e. graphics, charts, figures, formula, etc).

Question 2:

Provide a 3-section summary report (no less than 250 words per section) discussing the following clustering techniques:

1. BIRCH
2. CURE
3. MST

Provide the definition and background of each technique, the algorithm used, strengths, and weaknesses. Please cite your sources using APA references (points deducted for missing or improper formatting) . Please provide references in APA format.

Question 3:

Write a 2-3 page case study on a business and its use of anomaly detection. Provide some background on the business such as name and industry the business is in. Also provide the problems or issues the business has experienced that would require the use of anomaly detection. Provide methods and/or techniques used in the detection of the anomaly. Finally provide the solutions, if any, the business use to combat future instances of the anomaly. Please provide references in APA format.

Paper should be at least 500 words