Regresi Linier: Difference between revisions
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Persamaan Matematik yang ingin di tebak | |||
y = a + b*x | |||
Data yang di ketahui (pasangan) | |||
x1, y1 | |||
x2, y2 | |||
x3, y3 | |||
x4, y4 | |||
==Training== | |||
Kita ingin menebak a dan b. | |||
[[File:Linear-regression.png|center|400px|thumb]] | [[File:Linear-regression.png|center|400px|thumb]] | ||
Kita ingin menebak w0 dan w1 | |||
[[File:Simple regression.png|center|400px|thumb]] | |||
Gradient Decent = slope sama dengan NOL saat error minimal. | |||
==Prediction== | |||
Setelah a dan b di ketahui. | |||
Untuk | |||
x -> y (prediction) | |||
==Neural Network sebagai Regresi Linear== | |||
[[File:Neural-network-linear-regression.jpg|center|500px|thumb]] | |||
==Pranala Menarik== | ==Pranala Menarik== | ||
* [[Keras]] | * [[Keras]] | ||
Latest revision as of 22:57, 11 March 2020
Persamaan Matematik yang ingin di tebak
y = a + b*x
Data yang di ketahui (pasangan)
x1, y1 x2, y2 x3, y3 x4, y4
Training
Kita ingin menebak a dan b.
Kita ingin menebak w0 dan w1
Gradient Decent = slope sama dengan NOL saat error minimal.
Prediction
Setelah a dan b di ketahui. Untuk
x -> y (prediction)
Neural Network sebagai Regresi Linear
