Manually train a linear function he (x) =based on the followingtraining instances using stochastic gradient descent algorithm. The initial values ofparameters are 80 = 0.1,0₁ = 0.1, 0₂ = 0.1. The learning rate a is 0.1. Pleaseupdate each parameter at least five times.X10011x₂0101y2334

Answered: Manually train a linear function he (x)…

College Physics

11th Edition

ISBN:9781305952300

Author:Raymond A. Serway, Chris Vuille

Publisher:Raymond A. Serway, Chris Vuille

Chapter1: Units, Trigonometry. And Vectors

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Manually train a linear function he (x) =
based on the following
training instances using stochastic gradient descent algorithm. The initial values of
parameters are 80 = 0.1,0₁ = 0.1, 0₂ = 0.1. The learning rate a is 0.1. Please
update each parameter at least five times.
X1
0
0
1
1
x₂
0
1
0
1
y
2
3
3
4

Expert Solution

Step 1 The answer provided below has been developed in a clear step by step manner;

First of all we have to write Gradient Descent algorithm. Here I'm choosing python language because there is no given language in your query.

Gradient Descent algorithm:- #1. Import All Libraries import mumpy as np import pandas as pd from sklearn. linear_model import Linear Regression import math.

#2. Train Model Using Sklearn def predict_using_sklean(): df = pd.read_csv("test.csv") r = LinearRegression() r.fit(df[['x1','x2']],df.y) print(r.intercept_) return r.coef_, r.intercept_ predict_using_sklean() #Output:

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