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Machine Learning

Course Assignment

机器学习assignment代写 The assignment is to evaluate and describe a strategy based on predictions generated by a machine learning model.Part 1: Model···

The assignment is to evaluate and describe a strategy based on predictions generated by a machine learning model.

Part 1: Model Evaluation  机器学习assignment代写

 Using the test predictions provided

• Generatethe Lift Chat and PR Curve for the attached predictions
  • Togenerate the lift chart (using the Predictions vs Actuals Spreadsheet):
    1. Rank-orderthe data based on predictions (highest to lowest probability)
    2. Calculatethe cumulative sum of actuals for each row (e.g. at row 20 calculate the total sum of “1’s” in the actual column)
    3. Dividethe cumulative sum by the total number of positive examples
    4. Plotthe ordinal value of the sorted data on the x-axis, and the cumulative percentages on the y-axis
  • Togenerate the PR Curve:

1. Rank-orderthe data based on predictions (highest to lowest probability)
2. Calculateprecision as defined in the lectures
3. Calculaterecall as defined in the lectures
4. Plotthe PR-curve (precision vs recall)

• Referto the example spreadsheet as needed

Part 2: Next Steps  机器学习assignment代写

• As in the example, generate the profit curves (you can follow the example in the “Life Chart Exercise_example”spreadsheet to guide you, and use similar assumptions (e.g. expected profit / loss for a good / bad customer): the profit curve shows the expected profit that can be made from using the model to accept all customers below a certain prediction cut-off
• Estimatethe optimal probability cut-off to use when the model goes into
• Inone page or less, make a recommendation on how the strategy can be improved (e.g. by building other models beyond pure credit risk)
• For one of the additional models recommended, describe how the model can be integrated with businessstrategy (i.e. how a score will be converted into an action), how the model can be evaluated, and what potential risks or biases exist.

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