59 lines
5.7 KiB
Python
59 lines
5.7 KiB
Python
"""
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A simple wrapper for linear regression. (c) 2015 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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"""
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import numpy as np
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class LinRegLearner(object):
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def __init__(self, verbose = False):
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pass # move along, these aren't the drones you're looking for
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def author(self):
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return 'tb34' # replace tb34 with your Georgia Tech username
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def addEvidence(self,dataX,dataY):
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"""
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@summary: Add training data to learner
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@param dataX: X values of data to add
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@param dataY: the Y training values
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"""
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# slap on 1s column so linear regression finds a constant term
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newdataX = np.ones([dataX.shape[0],dataX.shape[1]+1])
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newdataX[:,0:dataX.shape[1]]=dataX
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# build and save the model
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self.model_coefs, residuals, rank, s = np.linalg.lstsq(newdataX, dataY, rcond=None)
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def query(self,points):
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"""
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@summary: Estimate a set of test points given the model we built.
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@param points: should be a numpy array with each row corresponding to a specific query.
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@returns the estimated values according to the saved model.
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"""
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return (self.model_coefs[:-1] * points).sum(axis = 1) + self.model_coefs[-1]
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if __name__=="__main__":
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print("the secret clue is 'zzyzx'")
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