Reference no: EM131085253
Question 1. Using Weka, apply the following algorithms (all under meta) on Heart Data using only the popular 14 attributes [#3 (age) , #4 (sex) , #9 (cp), #10 (trestbps) , #12 (chol) , #16 (fbs), #19 (restecg) , #32 (thalach), #38 (exang) , #40 (oldpeak) , #41 (slope) , #44 (ca), #51 (thal), #58 (num) (the predicted attribute)], and classify the given unknown instances.
An exciting and potentially far-reaching development in computer science is the invention and application of methods of machine learning (ML). These enable a computer program to automatically analyse a large body of data and decide what information is most relevant. This crystallised information can then be used to automatically make predictions or to help people make decisions faster and more accurately.
Project Objectives
Our objectives are to
- make ML techniques generally available;
- apply them to practical problems that matter to New Zealand industry;
- develop new machine learning algorithms and give them to the world;
- contribute to a theoretical framework for the field.
i. AdaBoostM1
ii. Bagging
iii. Randomcommittee
iv. LogitBoost
v. MultiBoostAB
vi. Dagging
vii. RandomTree (under trees)
Present the data in a tabular form with output from each of the 7 classifiers for the unknown instances. Finally, rank the classifiers based on their accuracy. If you need to perform any data transformation for a classifier, please do so.
What to submit? Submit a pdf file with your answers via the Blackboard. Your output should look like this:
Name Course HW#
Q1. Work and results for Q1
Q2. Work and results for Q2
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