m Maximize Σ di = s.t. i=1 WTwo 1+8; for all i with y₁ = 1 Wi+wo-di for all i with y₁ = 0 -Lw;≤LER, 8; ≥ 0 Here, instead of trying to maximize the buffer, we try to find coefficients that map/sepa- rate dat a either above 1 or below 0, with our objective to maximize this separation. We want to make each d; as large and positive as possible so that the real events get a predicted value of 1+8; 1 and false events get a predicted value of -80. L provides an appropriate bound on the coefficients of the hyperplane which you may need to try different values of to experiment. If you're not sure where to start, try L = 5.
m Maximize Σ di = s.t. i=1 WTwo 1+8; for all i with y₁ = 1 Wi+wo-di for all i with y₁ = 0 -Lw;≤LER, 8; ≥ 0 Here, instead of trying to maximize the buffer, we try to find coefficients that map/sepa- rate dat a either above 1 or below 0, with our objective to maximize this separation. We want to make each d; as large and positive as possible so that the real events get a predicted value of 1+8; 1 and false events get a predicted value of -80. L provides an appropriate bound on the coefficients of the hyperplane which you may need to try different values of to experiment. If you're not sure where to start, try L = 5.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
we are given a text file of 1000 points of data. Please write code that can take that data and put it through and seperate it using the attached linear
Transcribed Image Text:m
Maximize Σ di
=
s.t.
i=1
WTwo 1+8;
for all i with y₁ = 1
Wi+wo-di
for all i with y₁ = 0
-Lw;≤LER, 8; ≥ 0
Here, instead of trying to maximize the buffer, we try to find coefficients that map/sepa-
rate dat a either above 1 or below 0, with our objective to maximize this separation. We want
to make each d; as large and positive as possible so that the real events get a predicted value
of 1+8; 1 and false events get a predicted value of -80. L provides an appropriate
bound on the coefficients of the hyperplane which you may need to try different values of to
experiment. If you're not sure where to start, try L = 5.
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