53 lines
5.0 KiB
Python
53 lines
5.0 KiB
Python
"""
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template for generating data to fool learners (c) 2016 Tucker Balch
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Copyright 2018, Georgia Institute of Technology (Georgia Tech)
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Atlanta, Georgia 30332
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All Rights Reserved
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Template code for CS 4646/7646
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Georgia Tech asserts copyright ownership of this template and all derivative
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works, including solutions to the projects assigned in this course. Students
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and other users of this template code are advised not to share it with others
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or to make it available on publicly viewable websites including repositories
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such as github and gitlab. This copyright statement should not be removed
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or edited.
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We do grant permission to share solutions privately with non-students such
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as potential employers. However, sharing with other current or future
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students of CS 7646 is prohibited and subject to being investigated as a
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GT honor code violation.
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-----do not edit anything above this line---
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Student Name: Tucker Balch (replace with your name)
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GT User ID: tb34 (replace with your User ID)
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GT ID: 900897987 (replace with your GT ID)
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"""
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import numpy as np
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import math
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# this function should return a dataset (X and Y) that will work
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# better for linear regression than decision trees
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def best4LinReg(seed=1489683273):
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np.random.seed(seed)
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X = np.zeros((100,2))
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Y = np.random.random(size = (100,))*200-100
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# Here's is an example of creating a Y from randomly generated
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# X with multiple columns
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# Y = X[:,0] + np.sin(X[:,1]) + X[:,2]**2 + X[:,3]**3
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return X, Y
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def best4DT(seed=1489683273):
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np.random.seed(seed)
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X = np.zeros((100,2))
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Y = np.random.random(size = (100,))*200-100
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return X, Y
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def author():
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return 'tb34' #Change this to your user ID
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if __name__=="__main__":
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print("they call me Tim.")
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