2023年11月25日

Python代写 | CS 486 – Data Challenge

本次Python代写是创建一个模型来预测航班延误

CS 486 – Data Challenge

Background
The goal of this data challenge is to demonstrate your understanding of general machine learning by
predicting the outcome on a dataset. In answering the question:
1. You are allowed (and expected to) use external packages and libraries (eg. scikit-learn,
matplotlib, pandas).
2. You are allowed to consult external sources (notes, etc.)
3. You are allowed to discuss your model’s performance and general ideas
… but you are not allowed to discuss specific solutions with others inside or outside the course.
You are required to document your findings and explain your choices. You may use a Jupyter notebook or
a Python script. Any plots (charts, graphs) you create in terms of documenting or explaining must be
constructed using matplotlib or must have approval from the instructor. Work hard, and have fun!
Flight Delays
This task requires that you create a model to predict flight delays. The dataset comes from the Bureau of
Transportation Statistics; however, you are only to use the data found at the link here. (This file is 452
MB. Contact the instructor if you need a smaller version of this file.) The columns in the data file are as
follows:
● MONTH
● DAY_OF_WEEK
● FL_DATE (flight date)
● UNIQUE_CARRIER
● FL_NUM (flight number)
● ORIGIN (airport code)
● ORIGIN_CITY_NAME
● DEST (airport code)
● DEST_CITY_NAME
● CRS_DEP_TIME (departure time)
● ARR_DEL15 (arrival delay greater than 15 minutes — the target)
● CRS_ELAPSED_TIME
● DISTANCE (miles between origin and destination)