You are working in a team of business analysts at a large company in the present day. The “AdaBoost” algorithm was only published a few weeks ago and has not been widely implemented yet.
data mining
Description
Assignment Description
Context: You are working in a team of business
analysts at a large company in the present day. The “AdaBoost” algorithm was
only published a few weeks ago and has not been widely implemented yet. The
management of your company wants your team to research whether this algorithm
could be used to replace an existing classifier which is used in some parts of
the business. Your task is to implement the AdaBoost algorithm, provide a
technical report that explores the performance characteristics of your
implementation and a separate executive briefing that
provides a summary of your findings and a
recommendation about its use in the business.
AdaBoost Implementation
Implement the Adaboost algorithm as described in Week
5. Your implementation must be in Python. You may use existing packages to
implement your weak learners e.g. the use decision trees from sklearn. Your
implementation must be sklearn compatible. In short you must write a custom
AdaBoost class that implements both fit and predict functions. To confirm
compatibility, we will use the check_estimator
function from sklearn.
Notes:
You can read the full requirements and
details here https://scikitlearn.
org/stable/developers/develop.html (https://scikitlearn.
org/stable/developers/develop.html)
Your code must be documented using
Numpy/Scipy style docstrings
https://realpython.com/documenting-python-code/
(https://realpython.com/documenting-python-code/)
Technical Report (15 page max)
Your report should provide:
outline of the algorithm
a comprehensive analysis and discussion of
the performance characteristics of your algorithm, including:
analysis of all hyper-parameters on a synthetic
dataset (or multiple synthetic datasets)
comparison of your implementation on real or benchmark
datasets to:
the sklearn AdaBoost implementation
other standard classifiers of your choice
