Assignment 9
Total: 35 Points
General Instruction
• I recommend you can write your answer using LATEX.
• Submit uncompressed file(s) in the Dropbox folder via BeachBoard (Not email).
1. Using scikit learn, evaluate the classification accuracy of the decision tree, bagging,
AdaBoost, and Random forest.
(a) Find the Assn9.py and use the ‘Gini’ index as the criterion.
(b) (5 points) Complete the method decision tree that generate a decision tree from
X train, y train and predict y from X test. This method should record its prediction accuracy at tree score.
(c) (10 points) Similarly, complete the method bagging that generate multiple decision
trees using the bagging. This method should record its prediction accuracy at
bagging score by varying the parameter n estimators. Draw a chart whose Xaxis is n estimators and Y-axis bagging score, and the chart should have more
than 20 data points of different X-axis values.
(d) (5 points) Similarly, complete the method boost that generate multiple decision
trees using the AdaBoost. Draw a chart whose X-axis is n estimators and Yaxis boost score, and the chart should have more than 20 data points of different
X-axis values.
(e) (15 points) Similarly, complete the method forest that generate multiple decision
trees using the random forest. Draw a chart whose X-axis is n estimators, Y-axis
max features, and Z-axis forest score. The chart should have more than 100
data points of different pair of X-axis and Y-axis values.
(f) Submit your Assn9.py and a report that includes the charts.
